Monetary Policy Report - Central Bank of Argentina...Monetary Policy Report | October 2017 7 2....

Monetary Policy Report October 2017

Monetary Policy Report October 2017 ISSN 2313-9552 Online edition Publication date | October 2017 Central Bank of Argentina Reconquista 266 (C1003ABF) Ciudad Autónoma de Buenos Aires República Argentina Tel. | (54 11) 4000-1205 Web site | www.bcra.gob.ar Contents and edition | Economic Research Deputy General Management Publishing design | Communication Senior Management The contents of this report may be reproduced freely provided the source is acknowledged

For questions or comments please contact: [email protected]

Preface

As established in its Charter, the goal of the Central Bank of Argentina “is to promote monetary and financial

stability, employment, and economic development with social equity, to the extent of its powers and within

the framework of the policies implemented by the National Government”.

Without prejudice to the use of other, more specific instruments for complying with the rest of its mandates

—such as financial regulation and oversight, exchange market regulation, and innovation in savings, credit,

and means of payment instruments—, the main contribution that the monetary policy may offer to fulfill the

monetary authority’s mandates is to focus on price stability.

When inflation is low and stable, financial entities are able to better estimate their risks, which ensures higher

financial stability. Moreover, higher predictability allows producers and employers to create, endeavor,

produce and hire, which fosters investment and employment. Lastly, low income families may preserve the

value of their income and savings, which enables economic development with social equity.

The contribution of low and stable inflation to these objectives is never as evident as when it does not exist:

the flight from local currency may disrupt the financial system and lead to a crisis, the destruction of the price

system hinders productivity and genuine job creation, the inflation tax hits the most vulnerable families and

brings about redistribution of wealth that favor the most affluent segments of society. Low and stable

inflation, on the other hand, prevents all of these problems.

In line with this vision, the BCRA has formally adopted an Inflation Targeting Regime, effective as from

January 2017. As part of this new regime, the BCRA now releases its quarterly Monetary Policy Report. The

report’s main objectives are to communicate to the society the BCRA’s perspective of the recent inflationary

dynamic and its projection of price evolution, as well as to explain in a transparent manner its monetary

policy decisions.

Autonomous City of Buenos Aires, October 18th, 2017.

Contents

| 1. Monetary Policy: Evaluation and Perspectives Page 7 | 2. International Context Page 15 | 3. Economic Activity Page 27 | Exhibit 1 / Floating exchange rate and current account volatility Page 30 | Exhibit 2 / An association between the cash use intensiveness and construction activity Page 32 | Exhibit 3 / Public Private Partnership (PPP) Page 35 | 4. Prices Page 42 | Exhibit 4 / Mixed-Frequency Model Forecasts Page 45 | 5. Monetary Policy Page 55 | Exhibit 5 / Israel’s Inflation Targeting Experience Page 57 | Exhibit 6 / Tracing the mortgage market through Internet searches Page 62 | Abbreviations and Acronyms

Monetary Policy Report | October 2017

5

1. Monetary Policy: Evaluation and Perspectives The Inflation Targeting Regime launched in September, 2016, has made it possible to consolidate, for the first time in a long while, decreasing inflation expectations for the next two years. The targets are 10 percent ± 2 percent in 2018 and 5 percent ± 1.5 percent in 2019. In spite of this substantial achievement, there are persistent challenges regarding the pace of the disinflation process, which continues to exceed what is pursued by the monetary authority. During the third quarter, the average monthly inflation was 1.7 percent, a marginal decrease regarding that of the second quarter, of 1.8 percent. It is the lowest quarterly inflation rate, in the three-month moving average, since May, 2011. In addition, a greater regional dispersion was verified versus the first two quarters of the year. As for year-on-year inflation, it decreased to 22.7 percent (Q3-17), and it is virtually half of the year-on-year record against last year. Up to September, retail prices show a cumulative rise of 17.6 percent, with a core component which amounted to 16.1 percent and maintains some persistence in monthly records. According to the Market Expectations Survey (REM), expectations show a level of 22 percent for 2017, 15.8 percent for 2018, and 11 percent for 2019.

Even though core inflation is decreasing, it is not at the expected pace. This is why, from the beginning of the second quarter of the year, the Central Bank identified the persistence of the core inflation as a challenge to the ongoing disinflation process. In line with this diagnosis, in the third quarter of the year, the anti-inflationary bias of the monetary policy was emphasized. Although the 7-day repo rate continued at 26.25 percent, two factors account for the higher anti-inflationary bias. First, the ex ante real interest rate rise which takes place when the same nominal rate is accompanied by a drop in expected inflation rates. Second, a reduction of liquidity of the

Figure 1 | Core inflation rate. National and regional

1.7

1.7 1.7

1.7 1.8

1.7 1.7

1.7 1.8

1.6

1.5

1.9

1.8

1.7

1.6 1.7

1.6

1.5

1.3

1.5

1.5

0.0

0.4

0.8

1.2

1.6

2.0

National GreaterBuenos Aires

Pampeana Northwest Northeast Cuyo Patagonia

m.o.m. % avg. chg. Q1‐17 Q2‐17 Q3‐17

1.74

Source: INDEC

Q4‐16 (GBA)

CENTRAL BANK OF ARGENTINA

6

economy through operations carried out by the monetary authority which were reflected in a marked change in the yield curve slope of the LEBAC, which were based on both cutoff rates determined in the biddings and the BCRA activity in the secondary market. This deliberate action brings the benefit of extending the liabilities stock average term, which allows an easier management of the monetary authority's balance sheet and reduces the uncertainty associated with certain maturities. The transmission to the market rates reflected the anti-inflationary goal pursued by the monetary policy.

The economic activity expansion rate in the third quarter was around 4 percent year-on-year thus the GDP exceeds its previous peak. Unlike other recent cycles, the current expansionary phase is achieved with higher investment intensity. The reforms that have been introduced since December 2015 have led to a reduction in capital cost, and reduced uncertainty broadens families' and companies' planning horizons. These elements ensure a broader expansionary cycle than the preceding ones. The REM data confirm the expectation for 2018 that the economy will continue on this growth path, breaking the cycle which lasted six consecutive years where an expansion year was followed by a contraction year. Combined with the projected results for activity and inflation, the biennium 2017-2018 is expected to be the first one since 2003-2004 where a decrease in the inflation rate and an increase in the activity level occur simultaneously.

Figure 2 | | BCRA LEBAC secondary market yield curve

23.5

24.0

24.5

25.0

25.5

26.0

26.5

27.0

27.5

28.0

0 30 60 90 120 150 180 210 240 270 300

29‐Sep‐17

31‐Aug‐17

30‐Jun‐17

APR; %

daysSource: BCRA


7

2. International Context The international context affects Argentina mainly through three channels. Firstly, the global activity level has a direct impact on our foreign trade and potential flow of external investment. Secondly, the international credit markets situation affects the cost of sovereign indebtedness and the cost of private projects financing. Finally, the terms of trade have an impact on our foreign trade, affecting wealth levels and incentives to produce, consume, and invest. The world economic activity continued to improve in the last few months, both in advanced and emerging countries, in a context of lower volatility in financial markets. Among Argentina's main commercial partners, an improvement in the activity level is observed. Projections for the remainder of 2017 and for 2018 show that the activity level dynamism will be maintained, both at a global level and in the case of our commercial partners (see Figure 2.1). This would have a positive impact on Argentina (see Section 3.2.2.). In addition, credit conditions continue to be favorable for Argentina, both for the public and the corporate sectors. Meanwhile, the prices of the main export commodities in Argentina remained stable in the last few months and the multilateral real exchange rate depreciated by 9 percent in the third quarter of the year. The main risk that could alter this scenario is related to the impact on financial markets that could occur as a consequence of potential protectionist measures regarding the Brexit, or the lack of agreement regarding the revision of NAFTA. Besides, geopolitical tension in the Korean Peninsula (and to a lesser extent, the Iberian Peninsula) could also affect this scenario.

2.1 The Recovery of our Commercial Partners' Activity The available activity leading indicators for the main economies show, in all the cases, levels that are consistent with an economic activity expansion, and in most cases, they are better than those observed in

Figure 2.1 | Argentina's main trading partners growth


8

the previous IPOM. On the other hand, a lower inflation in the United States and the euro area, partly associated with the fall in oil prices, reverted after the increase in oil prices in the last months (a 20 percent increase since the previous lowest level in mid June). Thus, the inflation rate of the advanced economies showed an increasing trend in the last few months, approaching the monetary authorities’ goal1 in both economies, and surpassing it by almost 1 percentage point in the case of the United Kingdom (see Figure 2.2).

Regarding Brazil, Argentina's main commercial partner2 and a determinant factor in the region's economic performance, its activity level continues to show recovery signs, strengthening the trend described in the July, 2017 IPOM. In particular, the GDP showed the second consecutive rise in the second quarter (0.2 percent compared to the previous quarter, seasonally adjusted), while the Economic Activity Index prepared by the Central Bank of Brazil (BCB, see Figure 2.3) showed in July the highest growth in more than three years (1.5 percent, seasonally adjusted). In turn, in July, the Industrial Production Index recorded the third consecutive positive growth rate (for the first time since 2013) with a 2.5 percent year-on-year increase. The IMF forecasts a Brazilian GDP growth of 0.7 percent and 1.5 percent for 2017 and 2018, respectively 3 (a 0.5 percentage points and –0.2 percentage points change compared to last April). Should these forecasts be materialized, they would have a positive impact on bilateral trade, in a context where the bilateral exchange rate (Argentine peso-Brazilian real) has accumulated a 14 percent depreciation in 2017

1 The United States Federal Reserve (the Fed) does not follow a traditional Inflation Targeting Regime (nor does the European Central Bank, ECB). In compliance with its mandate, the Fed must promote the "highest" level of employment, moderate long-term interest rate, and stable prices goals. As regards the stable prices goal, in the Federal Open Market Committee (FOMC) meeting on January 25, 2012, a 2 percent annual variation target was set for personal consumption expenditures (PCE) in the long term. The ECB pursues price stability, defined as a lower than 2 percent inflation (but close to that value). 2 See Argentina's main commercial partners in the National Institute of Statistics and Census (INDEC). 3 In all the cases in this chapter, growth projections for the countries that are analyzed are taken from the IMF World Economic Outlook of October, 2017.

Figure 2.2 | Manufactured Purchasing Managers Index and inflation

38

42

46

50

54

58

62

66

Sep‐15 May‐16 Jan‐17 Sep‐17

Euro zone JapanUnited Kingdom BrazilUnited States RussiaIndia China

Contraction expectations

Expansion expectations

points

Manufactured Purchasing Managers Index in main economies

Source: Datastream

‐1

0

1

2

3

Sep‐15 May‐16 Jan‐17 Sep‐17

Euro zoneUnited KingdomUnited StatesJapan

y.o.y. % chg.

Inflation in advanced economies


9

(7.2 percent in real terms). The higher growth of the Brazilian GDP that is forecasted for 2018 would contribute in 0.14 percentage points to Argentine GDP growth in 2018 only through the trade channel.4

This evolution of the Brazilian activity level occurred in a context of marked disinflation, allowing an aggressive reduction of the monetary policy rate (the Selic rate target). Thus this variable reached 8.25 percent, 200 basis points lower than its value in June, 2017. According to the Focus survey, new reductions in the monetary policy rate are expected before the end of the year, by 125 additional basis points. In addition, since the inflation expectations were reduced by less than the monetary policy rate, the real interest rate also experienced significant reductions. In the euro area, the second Argentine export destination, both growth data of the second quarter and the leading indicators (see Figure 2.2), as well as projections for the remainder of the year and for 2018, continue showing a consolidation of the recovery. The seasonally adjusted GDP grew in the second quarter by 0.6 percent compared to the previous quarter. In year-on-year terms, the activity level increased by 2.1 percent, the highest rate since the first quarter of 2011. As for the Purchasing Managers’ Index (PMI) of the manufacturing sector (a leading indicator of industrial production), in September it recorded the highest value since 2011 as well. The last IMF projections show that a 2.1 percent and 1.9 percent growth is expected for 2017 and 2018 (0.4 percentage points and 0.3 percentage points more than the previous projection, respectively). In this context, the ECB decided to maintain its monetary policy rate in the zero percent historical floor, with an inflation rate below the target (lower than 2 percent). By the end of October, the ECB is expected to start discussing possible reductions to its asset purchase programme. The growth of the United States economy, the third Argentine export destination, accelerated to 3.1 percent (year-on-year) in the second quarter, above the market projections, in a context of a lower job creation in the last months. In spite of this, the unemployment rate (4.4 percent in August) is almost in its

4 See Brasil y su Efecto en la Actividad Argentina: una Mirada al Canal Comercial, in Ideas de Peso. As stated therein, this estimation is one of the most conservative ones, while there others which anticipate a greater impact.

Figure 2.3 | Brazil. Macroeconomics indicators

‐8

‐6

‐4

‐2

0

2

4

6

8

10

0

2

4

6

8

10

12

14

16

Jan‐13 Jul‐13 Jan‐14 Jul‐14 Jan‐15 Jul‐15 Jan‐16 Jul‐16 Jan‐17 Jul‐17

%Policy interest rate

Inflation ratePolicy real interest rate

Economic activity index (right axis)

y.o.y. % chg.

Source: Central Bank of Brazil


10

lowest level since 2001, and below the estimated values for the Non-Accelerating Inflation Rate of Unemployment (NAIRU, see Figure 2.4). Since the work factor would have a reduced growth potential and, according to some authors5, both the return on capital rate and the total productivity of the factors are in historically low levels, the United States growth rate could be lower in the next years than in the recent past. In turn, once again the IMF reduced (after the previous reduction in April) the growth projections for 2017 and 2018 to 2.2 percent and 2.3 percent (a 0.1 percentage points and 0.2 percentage points reduction, respectively), mainly due to lack of fiscal stimulus measures. Furthermore, the Fed's FOMC announced in its September meeting that in October it would begin its balance sheet normalization program6, which in practice means a less expansionary bias of the monetary policy. For the remaining of 2017, a new increase is expected in its reference interest rate, which at the end of the year would be in the range of 1.25-1.5 percent.

As regards China, the main Argentine export destination for primary products, this country is expected to end 2017 with a year-on-year GDP growth of 6.8 percent (0.2 percentage points more than the previous projection). The economy dynamism stands out during the first semester, partially linked to the postponement of reforms to correct the fiscal deficit, which reached 3.6 percent of the GDP in 2016, and to the high public investment rate. An increase in imports was also observed in the last months, which would end the year with a year-on-year increase of 11.2 percent, partly driven by a 5 percent appreciation of the yuan. Finally, for 2018, a lower GDP growth rate is expected, at around 6.5 percent.

5 See, for example, Martin Eichenbaum's presentation in the BCRA 2017 Jornadas Monetarias y Bancarias (Monetary and Banking Conference). 6 For more information, see the corresponding Fed document published in its web site.

Figure 2.4 | United States. Unemployment indicators

2

3

4

5

6

7

8

9

10

11

Jan‐49 Jan‐56 Jan‐63 Jan‐70 Jan‐77 Jan‐84 Jan‐91 Jan‐98 Jan‐05 Jan‐12

%

Source: FRED Economic Data, Federal Reserve Bank of St. Louis.

Recession Unemployment rate NAIRU


11

2.2 Favorable Credit Conditions for Argentina International financial markets continued —in general— with a period of improvement and lower volatility, both for debt and equity assets, and in advanced and emerging economies. The Fed's announcement at the end of September about starting the reduction of their asset purchase program in October, together with the fact that the ECB may start discussing this issue soon, had a limited impact on the markets, particularly on sovereign debt markets (see Figure 2.5).

During the last months, the sovereign risk premiums continued their decreasing trend, remaining almost unchanged in the trimester for Latin America (see Figure 2.6).

Figure 2.5 | Stock indexes and 10 years sovereign bond yield

Figure 2.6 | Sovereign risk premium

‐1

0

1

2

3

4

Sep‐16 Jan‐17 May‐17 Sep‐17

United States GermanyUnited Kingdom SwitzerlandFrance JapanAustralia Canada

%

Source: Bloomberg *Global MSCI; **Emerging MSCI

85

90

95

100

105

110

115

120

125

Sep‐16 Jan‐17 May‐17 Sep‐17

Global stock indexes*United States (S&P500)Europe (EuroStoxx600)Japan (Nikkei)Emerging stock indexes**

Dec‐14=100Stock indexes Sovereign bond yield

Source: Bloomberg and IMF, World Economic Outlook

100

200

300

400

500

600

700

Jan‐16 Apr‐16 Jul‐16 Oct‐16 Jan‐17 Apr‐17 Jul‐17 Oct‐17

Emerging Europe Emerging Asia Latin America

b.p.


12

Debt issuance in emerging countries has increased, so far in 2017 compared to the same period in 2016, by 37 percent, where the corporate sector had both the highest share and the highest dynamism. For Argentina, credit conditions improved even more than for the rest of the emerging economies, with an Argentine country risk of around 360 basic points (b.p.) for the bond index EMBI+AR, and 368 b.p. for the corporate bond index CEMBI+AR, in both cases, the lowest value in the last ten years (see Figure 2.7). The corporate risk differential was also reduced compared to other emerging economies (see Section 3.3). Therefore, the public sector and the Argentine corporate sector are being financed at lower interest rates in the international markets.

The Multilateral Real Exchange Rate Index (Índice de Tipo de Cambio Real Multilateral, ITCRM) depreciated by 8.7 percent in the quarter, driven both by the 9.9 percent depreciation of the Argentine peso against the US dollar and the 2.7 percent appreciation of the currencies of our commercial partners (also against the US dollar), and partly offset (3.9 percent) by the higher Argentine inflation compared to our commercial partners. The highest nominal (and real) depreciations of the Argentine peso were observed in July and August (see Figure 2.8).

Figure 2.7 | Risk Indicators

0

400

800

1,200

1,600

2,000

Oct‐07 Oct‐09 Oct‐11 Oct‐13 Oct‐15 Oct‐17

EMBI+ CEMBI+ EMBI+ Argentina CEMBI+ Argentina

b.p.

Source: Bloomberg


13

The Commodity Price Index (Índice de Precios de las Materias Primas, IPMP BCRA) —which reflects the evolution of the main Argentine export commodities, with a marked influence on the Argentine economic cycle— remained relatively stable in the last months (0.09 percent year-on-year variation). In the case of the agricultural BCRA IPMP, the decreasing trend of the last few months has continued (–20 percent compared to June, 2016), although during 2017 it has remained stable, apart from certain occasional volatility (see Figure 2.9).

Figure 2.8 | Decomposed real effective exchange rate index variation

Figure 2.9 | Commodity prices

‐8

‐6

‐4

‐2

0

2

4

6

8

10

Mar‐16 Jun‐16 Sep‐16 Dec‐16 Mar‐17 Jun‐17 Sep‐17

m.o.m. % chg. DeflatorsAppreciation against currencies of the commercial partnersNominal exchange rate $/US$ITCRM

Source: BCRA

Real multilateral peso depreciation

Real multilateral peso appreciation

100

150

200

250

300

350

400

450

Sep‐02 Sep‐05 Sep‐08 Sep‐11 Sep‐14 Sep‐17

IPMP BCRA

Agricultural IPMP BCRA

Source: BCRA

Dec‐01=100current US$

175

225

275

325

375

Sep‐12 Sep‐13 Sep‐14 Sep‐15 Sep‐16 Sep‐17


14

Finally, the terms of trade (the Argentine export and import prices ratio)7 remained relatively stable in the last months, around the 2013–2017 average (with data up to August; see Figure 2.10).

To sum up, for the next few months, a sustained growth rate is expected at a global level, particularly in our main commercial partners, which would have a positive impact on the demand of Argentine exports. In addition, ample liquidity conditions will continue to exist for emerging countries, despite the tightening of the Fed's monetary policy, which would not have a significant impact on financing costs. Therefore, credit conditions for Argentina are expected to remain favorable. The main risks would be linked to the impact of protectionist measures on financial markets and to the geopolitical tension in the Korean Peninsula (and to a lesser extent, the Iberian Peninsula).

7 A fall in the terms of trade has a negative impact on the Argentine balance of trade, and an increase has a positive impact.

Figure 2.10 | Terms of Trade

90

100

110

120

130

140

150

160

Aug‐02 Aug‐05 Aug‐08 Aug‐11 Aug‐14 Aug‐17

2004=100

Source: INDEC

Average 2013 ‐2017


15

3. Economic Activity In the third quarter, the expansion recorded in the last 12 months, at a rate of about 4 percent yearly, brought GDP higher than the highest level of 2015. The new economic configuration, coupled with the measures taken to strengthen macroeconomic stability, led to a reduction of capital costs and extended the planning horizon for companies and households. The current phase of growth is characterized by greater investment intensity, supplemented by widespread increases in employment at the sectoral level. Going forward, these trends will strengthen, and will allow the economy to leave the stagnation of the last six years behind.

3.1 Economic Growth Consolidates The structural reforms implemented starting in 2016, as well as the fiscal and monetary normalization of the economy, have been effective for the economic growth. This happens in a favorable international scenario, in which the economies of our trading partners grow (see Box) and there is an ample supply of liquidity in international financial markets. As anticipated in the last IPOM, the evolution of the Argentine economy continued to show features typical of growth cycles of Latin American countries. During the second quarter of the year, the components of domestic expenditure (consumption and investment) grew faster than income (GDP). As a result, net exports have dropped. The greater dynamism in domestic expenditure led to a recovery of the relative price in tradable and non-tradable goods.

Figure 3.1 | Economic activity

141

144

147

150

153

Sep‐14 Mar‐15 Sep‐15 Mar‐16 Sep‐16 Mar‐17 Sep‐17

EMAE s.a EMAE t.c. GDP s.a.

*Statistical carry‐forward for Q3‐17 from EMAE ‐ August data. Note: s.a.: seasonally adjusted. t.c.: trend‐cycle. EMAE: Monthly Economic Activity Indicator. Source: INDEC

2004=100

+1.2%*

+0,7%

+1,2%

+1,0%

+1%PCP‐BCRA

4% y.o.y.


16

Box. Synchrony in the Cycles of the Argentine Economy and its Trading Partners Starting in the middle of the 20th century, the Argentine business cycle has been mostly synchronized with those of its major export destinations.8 Indeed, the correlation between both series was 0.46 in the 1966–2016 period. Besides, historical evidence shows that the Argentine cycle has a greater degree of volatility: the standard deviation of the Argentine cycle is 3.5 times greater than the cycle of the group of its main trading partners (see Figure 3.2).

The divergence periods coincided with idiosyncratic disturbances that altered local activity. The most important were the Malvinas’ war and the return to democracy in 1982–1983, the hyperinflation crisis of 1989–1990, the beginning and the end of the currency convertibility regime, and, more recently, the establishment of pervasive foreign exchange controls (cepo), in 2012–2015 —which introduced distortions in the economy to its corresponding costs in terms of efficiency. After these disturbances, the Argentine cycle resumed its regular synchronicity.

During the second quarter of 2017, GDP grew at a yearly rate of 2.7 percent (0.7 percent seasonally adjusted), and expanded to a 3.8 percent yearly rate in the first half of the year. In July, the EMAE grew 0.7 percent seasonally adjusted, leaving a statistical carry-over effect of 1.2 percent, seasonally adjusted, for the third quarter (see Figure 3.1). By the third quarter, the GDP had surpassed the 2015 peak, completing one year of continuous growth with a year average of 4 percent. The last BCRA Contemporary GDP Forecast (PCP-BCRA) shows a quarterly increase of 0.95 percent, seasonally adjusted, while the projection of the Market Expectations Survey is 1.2 percent, seasonally adjusted. The index developed by the Undersecretariat of Macroeconomic Programming estimates a growth rate of 1.3 percent, seasonally adjusted. The data as of September of the Leading Activity Index (ILA) prepared by the BCRA, which anticipates turning points in the EMAE, suggests that the economy will continue to expand during the last quarter (see Figure 3.3). 8 The cycle of trading partners was computed as an chain arithmetic average with moving weights, based on those economies’ shares of Argentine exports. In 1966–1996, based on the information on total exports by O.J. Ferreres, the following economies were considered: Brazil, the United Kingdom, Chile, China, the Netherlands, Belgium, Germany, France, Italy, Spain, Uruguay, Bolivia, Japan, Mexico, Peru, Paraguay and the United States. For the 1997–2016 period, based on information by INDEC, the following economies were added: the remaining Euro area countries, Canada, Colombia, Algeria, Egypt, Indonesia, India, Iran and South Africa. Throughout the sample, these countries represented 66 percent of total exports.

Figure 3.2 | GDP Cycle - Argentina and the top export destinations

‐20

‐16

‐12

‐8

‐4

0

4

8

12

‐10

‐8

‐6

‐4

‐2

0

2

4

6

1967 1972 1977 1982 1987 1992 1997 2002 2007 2012 2017f

% of the trend% of the trend

Commercial partners

Argentina (right axis)

f: Forecast. Note: Trend estimation via Hodrick‐Prescott filter. Top export destinations (1960‐2016).Source: INDEC, O.Ferreres, World Bank and IMF


17

3.2 The Current Macroeconomic Configuration Breaks the Previous Stagnation The last six years were characterized by high output volatility around a stagnant trend9 (see Figure 3.4). This behavior revealed constraints in the factors that determine supply, until the end of 2015. The macroeconomic imbalances, the distortions in relative prices and exchange restrictions led to major falls in the investment rate, which led in turn to stagnation in potential GDP and productivity. Between July 2011 and July 2017, activity shows an average 0.4 percent yearly growth, below both population growth and the increase in total urban employment (1.1 percent), which created a constant deterioration of the per capita income.

9 Between December, 2011, and September, 2017, there were three full economic cycles, with various depths and durations. The recessive phase, which began in September, 2015, and ended in August, 2016, was less deep than the previous two.

Figure 3.3 | Leading indicator of economic activity

Figure 3.4 | Economic activity

Jun‐15

May‐16

turning pointSep‐15

125

130

135

140

145

150

155

Sep‐11 Sep‐12 Sep‐13 Sep‐14 Sep‐15 Sep‐16 Sep‐17

ILA

EMAE

Note: t.c.: trend‐cycle. Source: INDEC, Sectoral associations, Bloomberg and UTDT

EMAE t.c. 2004=100ILA s.a. Mar‐94=100

turning point Aug‐16

94

96

98

100

102

104

Jul‐11 Jul‐12 Jul‐13 Jul‐14 Jul‐15 Jul‐16 Jul‐17

2011=100 EMAE s.a. EMAE t.c.

Notes: EMAE: Monthly economic activity indicator; s.a.: seasonally‐adjusted. t.c.: trend‐cycle. Source: INDEC

maximum

minimum


18

The establishment of fiscal and inflation targets aimed at strengthening the macroeconomic environment, the settlement of the conflict with the holdouts, the normalization of the exchange market and the removal of distortions and taxes in international trade, among other measures, extended the planning horizon for agents and reduced the cost of capital. The corporate risk differential relative to other emerging economies is below 100 bp: the lowest level since 2010 (see Figure 3.5). This new macroeconomic configuration, together with the projected improvements in infrastructure, also increased the expected capital marginal return. Against that backdrop, the expansion of the economy, with a rate of approximately 4 percent year on year in 2017, with improvements in employment and a growing contribution of investment, will make it possible to leave behind the stagnation of the last years (see Subsections 3.2.1 and 3.2.3).

3.2.1 Investment Takes on a Prominent Role in the Current Phase In line with what was anticipated in the last IPOM, gross domestic fixed investment increased markedly during the second quarter (8.3 percent, seasonally adjusted, the highest growth rate since the second quarter of 2010). This performance made it possible to surpass the level at the start of the last recession (Q3-15). This recovery of investment was the most rapid and intense of the last four years, including that of 2009/10 (see Figure 3.6). For the third quarter, this trend is expected to continue, according to the Contemporary Investment Index, prepared by the Ministry of Treasury (5.1 percent, seasonally adjusted).

Figure 3.5 | Cost of capital

Figure 3.6 | Gross fixed investment. Last business cycles compared

250

300

350

400

450

500

550

600

650

May‐16 Jul‐16 Sep‐16 Dec‐16 Feb‐17 Apr‐17 Jun‐17 Aug‐17 Oct‐17

Sovereign

EMBI+ Argentina

EMBI+

b.p.

Source: Bloomberg

250

300

350

400

450

500

550

600

650

May‐16 Jul‐16 Sep‐16 Dec‐16 Feb‐17 Apr‐17 Jun‐17 Aug‐17 Oct‐17

Corporate

CEMBI Argentina

CEMBI Emerging

b.p.

Source: Bloomberg

Q2‐17104.8

Q3‐17f110.2

70

75

80

85

90

95

100

105

110

115

0 1 2 3 4 5 6 7 8

II‐08/II‐09

III‐11/II‐12

III‐13/III‐14

III‐15/III‐16

Peak / trough

f: Forecast. Note: Peaks and troughs were identified by Bry‐Boschan routine. Source: INDEC

quarters

IBIF s.a. (peak)=100


19

The growth of investment was noteworthy for the strong increase in expenditure in durable production equipment (EDP)10, which distinguishes the current recovery from previous ones. The increase in investment in durable production equipment during the second quarter had both a domestic (7.6 percent, not seasonally adjusted) and a foreign origin (7.8 percent, seasonally adjusted). According to FIEL, the index of domestic-origin equipment remained at high levels in July and August. In the same period, the imported volumes of capital goods reached a historic peak (an average 15.4 percent, seasonally adjusted), particularly in the case of foreign purchases of machinery and equipment. This dynamic behavior was reflected in the EDP-BCRA index, which anticipates an important growth of investment in durable production equipment during the third quarter (see Figure 3.7).

Construction continued to grow during the third quarter, boosted by private and public works, and is now nearing the peak reached in 2015. The delivery of cement to the domestic market grew 6.1 percent, not seasonally adjusted, between July and September, while the Construya index, which mainly captures those sectors related to the completion of private works, expanded 9.6 percent, seasonally adjusted (see Figure 3.8). 10 This includes machinery, equipment, and transport material.

Figure 3.7 | Investment in durable production equipment

30

40

50

60

70

80

90

100

110

120

Q3‐05 Q3‐07 Q3‐09 Q3‐11 Q3‐13 Q3‐15 Q3‐17

Investment in durable production equipment (EDP)

EDP‐BCRA Index

Source: INDEC and FIEL

level s.a.2011=100


20

3.2.2 Domestic Expenditure and Net Exports Showed Features Typically Associated with Expansion Phases Besides investment, private consumption accelerated (3.8 percent, seasonally adjusted), contributing 2.8 percentage points to GDP change11, surpassing the highest level before the recession (see Figure 3.9).

11 Public consumption also made a positive contribution (0.2 percentage points), with a 1.4 percent increase, not seasonally adjusted, in the second quarter.

Figure 3.8 | Construction activity evolution

Figure 3.9 | Expenditure components during the current recovery

‐30

‐20

‐10

0

10

20

30

Sep‐13 Sep‐14 Sep‐15 Sep‐16 Sep‐17

y.o.y. % chg.ISAC Wholesale cement deliveries

Construya Index Construction (EMAE)

Source: INDEC, AFCP and Grupo Construya

110.2

105.1

103.3

100.1

92

96

100

104

108

112

Q3‐15 Q4‐15 Q1‐16 Q2‐16 Q3‐16 Q4‐16 Q1‐17 Q2‐17 Q3‐17f

level s.a. Q3‐15=100

Investment

Private consumption

Public consumption

GDP

f: ForecastSource: INDEC


21

Various indicators show that this behavior continued during the third quarter, with a particularly strong growth in quarterly real gross VAT (2.9 percent, seasonally adjusted) and imports of consumer goods (15 percent, not seasonally adjusted) in July-August. Going forward, the Leading Private Consumption Indicator-BCRA12 projects that the positive trend will continue (see Figure 3.10). Private consumption was supported by the continued improvement in households’ real wages, employment expansion, and credit and public expenditure in social benefits, in a context in which the consumers’ trust is expanding. During the third quarter, consumer credit (personal loans and credit cards) grew 4.1 percent, seasonally adjusted, in real terms, and benefits of social security and social plans grew 4.5 percent, seasonally adjusted, between July and August.

As expected in an expansive phase of the economic cycle, the greater strength of investment and private consumption relative to income13 caused net exports to be negative and remain negative in the third quarter. Exports of goods and services fell 7.1 percent, seasonally adjusted, in the second quarter14, as was anticipated in the July IPOM, and they are estimated to have recovered during the third quarter, as suggested by July and August trade data. Imports grew 4.2 percent, seasonally adjusted, in the second quarter, with a significant performance of capital goods, a trend which continued between July and August.

12 For greater detail, see Exhibit 1/ Private consumption, a variable hard to track in real time, IPOM, July 2017. 13 See section 3.2 of the Economic activity chapter of the July, 2017, IPOM. 14 Mainly due to the delays in the commercialization of corn and soybean products caused by climatic factors, which affected exports of primary goods and agricultural manufactures.

Figure 3.10 | Private consumption evolution

360

400

440

480

520

560

125

135

145

155

165

175

Q3‐08 Q3‐09 Q3‐10 Q3‐11 Q3‐12 Q3‐13 Q3‐14 Q3‐15 Q3‐16 Q3‐17*

Mar‐94=100

Leading private consumption index ‐ BCRA

Private consumption (right axis)

billion $ (2004)

*Parcial data. Source: INDEC, UTDT, Ministry of Treasury and ADEFA


22

While pervasive foreign exchange controls were in place, total exports showed an unusual decoupling with the cycles of trading partners, a behavior which was normalized after the macroeconomic reconfiguration by the end of 2015 (see Figure 3.11). Starting in 2016, exports of industrial manufactures had one of the best performances of the economic cycle, compared to other recent boom-bust cycles (see Figure 3.12).

Figure 3.11 | Exports quantity and economic cycle of the commercial partners

Figure 3.12 | Industrial origin exports. Comparative of last economic cycles

‐3

‐2

‐1

0

1

2

3

100

105

110

115

120

125

130

2005 2007 2009 2011 2013 2015 2017*

% deviation against trend

exports(quantities 2004=100)

Total exports

Economic cycle of the commercial partners (right axis)

Source: INDEC, World Bank and IMF

Clamp

60

70

80

90

100

110

120

0 1 2 3 4 5 6 7 8

quarter

Q2‐08 / Q2‐09

Q3‐11 / Q2‐12

Q3‐13 / Q3‐14

Q3‐15 / Q3‐16*

*Data up to Aug‐17. Source: INDEC

Peak / troughquantities s.a. beginning of the recession (peak)=100


23

3.2.3 Growth in Activity and Employment was Widespread among Productive Sectors Growth in economic activity was widespread at the sectoral level. Some of the most dynamic sectors in the last years were fishing, construction, financial intermediation, agriculture, transport and communications. Construction continues to grow thanks to private and public works. Financial intermediation was boosted by the expected decrease in inflation, which makes it possible to expand the credit horizon, the implementation of measures aimed at facilitating the operation of the banking system15 and the strong demand of UVA credit, which grows at a 50 percent yearly rate. The agricultural sector continues to respond positively to the elimination/reduction of export duties and the normalization of the exchange market (see Figure 3.13).

The only sectors which underwent contractions —which account for 4.6 percent of the GDP— were electricity, gas and water, and mining and quarrying operations. In the first case, the residential demand was reduced by two factors: higher temperatures than the previous year and the removal of subsidies. In the second case, the current international price of oil was not profitable enough to break the declining trend in production seen since 1998, while the reduction in mining exploration in the last years affected sectoral activity negatively. As economic activity consolidates its growth, so does the number of productive sectors increasing their payroll. Sectoral diffusion of job creation in the private sector continued its growing trend during the second quarter, and appears to have remained at high levels in the third quarter (see Figure 3.14). 15 Lending and borrowing rates set by financial entities were liberalized. The possible uses for available lendable capacity in foreign currency were broadened, in order to avoid currency mismatches in balance sheets.

Figure 3.13 | Economic Growth by sectors. Second quarter 2017

‐6.9

‐2.2

0.4

1.0

1.0

1.1

1.7

2.2

2.5

3.3

4.0

4.4

4.9

9.7

‐12 ‐8 ‐4 0 4 8 12

Mining and quarrying

Electricity, water and gas

Other services

Public administration

Education

Real estate

Commerce

Scoial services and health

Indsutry

Hotels and restaurants

Transport and communications

Financial intermediation

Agriculture

Construction

Fishing

y.o.y. % chg.

Source: INDEC

19.5


24

Employment continued the positive trend begun one year ago, surpassing the previous peak. So far this year, it has accumulated a 1 percent gain, seasonally adjusted, (see Figure 3.15), led in the last 12 months by the performance improvement of private employment (1.5 percent year-on-year) relative to public employment (1.1 percent year-on-year).

Figure 3.14 | Growth diffusion of the private formal employment

Figure 3.15 | Evolution of formal employment. Seasonally adjusted

Jul‐12 Jan‐13 Jul‐13 Jan‐14 Jul‐14 Jan‐15 Jul‐15 Jan‐16 Jul‐16 Jan‐17 Jul‐17

4

6

8

10

12

14

number of economic sectors

Source: INDEC

7,600

7,900

8,200

8,500

8,800

10,800

11,100

11,400

11,700

12,000

Jul‐12 Jul‐13 Jul‐14 Jul‐15 Jul‐16 Jul‐17

thousand of employees

total employment

Private employment (right axis)

thousand of employees

Note: Total employment and private employment are expressed excluding workers linked to the social simplified tax regime for small business.Source: MTEySS


25

In terms of employment and unemployment rates, no significant variations were recorded in the last year.16 As the recovery of job creation was slightly slower than population growth, the employment rate was virtually unchanged. 3.3 Outlook: The Argentine Economy Is Expected to Resume a Path of Sustained Growth As a consequence of the new macroeconomic configuration, the BCRA expects for the economy to consolidate its growth process, leaving behind the trend of stagnation. This view is in line with the estimations contained in the 2018 National Budget Bill, which projects a growth of 3 percent for 2017 and 3.5 percent for 2018-2019, and is shared by the staff of the Market Expectation Surveys, who projected that the economy will continue to expand at yearly rates of 2.8 percent, 3 percent, and 3.2 percent between 2017 and 2019. This outlook implies a break, starting in 2016, in the medium-term growth trend of the GDP17 (see Figure 3.16.).

Greater macroeconomic certainty, together with a favorable growth outlook for the economy and productivity, coupled by the fall in the cost of capital, will continue to be critical in order to boost investment. Infrastructure development will be crucial to mobilize the economy’s productivity18. The Public-Private Partnership Law (P.P.P.), the productivity-based agreement for the exploitation of the Vaca

16 The rate difference is included in the sample error, according to INDEC. The population value in employment and unemployment rate fall within the confidence intervals of the second quarter of 2016, thus, it is inferred that both rates remained stable in the second quarters of 2016 and 2017. 17 Applying the Hodrick-Prescott filter (λ: 1600) to the projected GDP series based on the Market Expectations Survey forecasts for the 10, 25, 50, 75 and 90 percentiles, it is possible to see that, in all cases, the analysts assume an implicit break, starting in 2016, in the medium-term trend. 18 See Highways to Heaven: Infrastructure Determinants and Trends in Latin America and the Caribbean, IMF 2017.

Figure 3.16 | GDP. Trend of GDP projected using REM forecasts

300

400

500

600

700

800

Q1‐93Q1‐95 Q1‐97 Q1‐99Q1‐01 Q1‐03 Q1‐05Q1‐07 Q1‐09 Q1‐11Q1‐13 Q1‐15 Q1‐17Q1‐19

GDP s.a.

GDP trend up to Q2‐17

GDP trend projected using REM

Note: Trend estimates via Hodrick‐Prescott filter (λ=1600).Source: INDEC and REM‐BCRA

billion $, constant prices of 2004


26

Muerta field19, and the award of alternative energy projects in the context of the RenovAR program20 will enable the development of infrastructure, technology and energy projects, among others. According to data from the Office of the Chief of the Cabinet of Ministers, infrastructure investment will go from $269,417 million (2.6 percent of GDP) in 2017 to $436,313 million in 2018 (3.5 percent of GDP), a 50 percent increase in real term (see Exhibit 3 / Public-Private Partnerships). The great potential of UVA mortgage loans, in a context of low borrowing at household and companies21 (mortgage loans account for 0.9 percent of GDP in Argentina, versus 10 percent of GDP on average in other emerging economies), enables the development of real estate activities and construction. Empirical evidence suggests that it is possible to continue facilitating access to home financing through a robust legal framework and a stable macroeconomic environment.22 The improvement in the outlook for trading partners will boost external sales of industrial manufactures, which, together with record harvest, will lead to an expansion in exports. Consumption will continue to be supported by the growth in employment and the decrease in inflation, which improves purchasing power and has a positive impact on consumers’ confidence (see Figure 3.17.).

From a supply point of view, the use of productive factors is below the level that created inflation pressures, a behavior that will continue to be monitored by the BCRA.

19 This sectoral agreement enables an increase in productivity and a decrease in costs, projecting investments of $80 billion in 2017 and $140 billion in 2018, related to new drilling activity and the associated infrastructure. 20 Law 27191 classified as an activity of national interest the generation of power from renewable sources, aimed at supplying public services, and also all research for technological development and the manufacture of equipment for that purpose. Under rounds 1 and 1.5 of the tender for power generation capacity, private parties will invest US$4 billion to install over 2,400 MW of wind and solar power. 21 See the BCRA Financial Stability Report, first half of 2017, Exhibit 1. 22 Cerutti, Dagher and Dell'Ariccia, 2017, Housing finance and real-estate booms: a cross-country perspective. IMF staff discussion note, June 2015, and Warnock, V., and F. Warnock, 2012, “Developing Housing Finance Systems”, Reserve Bank of Australia Annual Conference Volume, Reserve Bank of Australia, Sydney.

Figure 3.17 | Consumer confidence index and Inflation

0

20

40

60

25

40

55

70

Jan‐13 Sep‐13 May‐14 Jan‐15 Sep‐15 May‐16 Jan‐17 Sep‐17

pointsAnnualized Biannual inflation (Nacional CPI‐Core)*

Consumer confidence index ‐ UTDT

*CPI Province of San Luis up to Jul‐12, then BA CPI upto apr‐16, then Greater Buenos Aires CPI up to Dic‐16 and INDEC´s CPI of national coverage last data.Source: UTDT, INDEC and Statistical offices of City of Buenos Aires and Province of San Luis

%


27

Exhibit 1 / Floating exchange rate and current account volatility Introduction Floating exchange rate regimes have the benefit of absorbing macroeconomic shocks, easing the internal balance of economy. Typically, there is an appreciation of the exchange rate when demand surpluses take place, as domestic goods becomes more expensive; and a corresponding depreciation under low demand conditions, when the prices of such goods decline. In order to study the automatic stabilizing role played by floating exchange rate regimes, this exhibit presents an empirical descriptive exercise that shows evidence about the performance —in terms of the current account’s volatility and balance— of the economies with floating exchange rate regimes during 2000-2013. Exercise There is extensive literature that develops alternative criteria for identifying exchange rate regimes. Some of such criteria are focused on which is the regime announced by policy authorities (de jure criteria), while others concentrate on those behaviors that were actually observed (de facto criteria). In this case, we will apply the methodology devised by Levy Yeyati and Sturzenegger (2001, 2003, 2005), who propose an exchange rate classification based on a cluster analysis in order to group countries in accordance with the relative volatility of their exchange rates and reserves, implementing a de facto selection criterion.23 Levy Yeyati and Sturzenegger (2016) extended the regime classification to the period 1974–2013, while broadening the sample of countries. By using this extended classification, we have identified those economies that adopted a floating regime during more than 70 percent of 2000–2013, which is the period under consideration.24 In this way, a sample made up of 29 economies with de facto floating regimes was obtained, all of them listed under Appendix A. There are two characteristics of this sample that must be highlighted. Firstly, it is heterogeneous in terms of the level of development reached by those economies. Secondly, the Euro area is considered as an aggregate, floating exchange rate economy, so its member states are excluded from the sample of economies in which floating regimes were not implemented.25 The sample of economies in which alternative regimes were adopted is shown in Appendix B, and includes 97 cases.

23 For a detailed description of the methodology, see the referenced text. 24 In order to determine floating exchange rate regimes, those economies classified as “float” in the first and second round of the method were considered. See Levy-Yeyati and Sturzenegger (2016). 25 In an alternative exercise, the Euro area countries were analyzed individually as cases of fixed exchange rate regimes, excluding the Euro area from the sampled floating exchange rate economies. The results obtained are not significantly different from those presented herein.


28

Figure 1 shows the relationship between the average current account balance, in product terms, and its volatility for each economy under consideration.

According to the analyzed sample, those economies under floating regimes experimented significantly lower current account volatility. The average standard deviation of economies under floating regimes reached 2.83 percent, while that of economies under other regimes was 5.23 percent. This lower volatility is associated to a lower prevalence of abrupt changes in the current account balance. In turn, economies under floating regimes showed a higher deficit in their average current account (-2.80 percent) against an average -2.06 percent in the remaining cases. Appendix A Albania, Armenia, Australia, Canada, Chile, Colombia, Czech Republic, Euro area, Hungary, India, Indonesia, Israel, Japan, Kenya, Kyrgyzstan, Madagascar, Mauricio, Mexico, Moldavia, Paraguay, Peru, Philippines, Poland, Serbia, Sweden, Tanzania, Thailand, United Kingdom, United States. Appendix B Algeria, Antigua and Barbuda, Argentina, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Cambodia, Cameroon, Cape Verde, China, Comoros, Democratic Republic of the Congo, Republic of Congo, Costa Rica, Côte d’Ivoire, Croatia, Denmark, Djibouti, Dominican Republic, Ecuador,

Figure 1 | Average and deviation of the current account balance (% of GDP). 2000-2013

Source: World Development Indicators –The World Bank, Eurostat,

Central Bureau of Statistics of Israel, Central Bank of Chile and OECD

0

5

10

15

20

25

‐40 ‐20 0 20 40

Average current account balance (% of GDP)

Other Floating regime

Stan

darddeviation (curren

t account balan

ce. (% ofGDP)


29

Egypt, El Salvador, Gabon, Gambia, Ghana, Guatemala, Guinea, Haiti, Honduras, Hong Kong, Iceland, Jamaica, Jordan, Kazakhstan, Republic of Korea, Lebanon, Liberia, Macao, Macedonia, Malawi, Malaysia, Mali, Mauritania, Mongolia, Montenegro, Morocco, Mozambique, Namibia, Nepal, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Qatar, Romania, Russian Federation, Rwanda, Saudi Arabia, Senegal, Sierra Leone, Singapore, South Africa, Sri Lanka, Sudan, Suriname, Swaziland, Switzerland, Syrian Arab Republic, Tajikistan, Togo, Trinidad and Tobago, Tunisia, Turkey, Uganda, Ukraine, United Arab Republic, Uruguay, Vanuatu, Bolivarian Republic of Venezuela, Vietnam, Zimbabwe. References Levy-Yeyati, E. and Sturzenegger. F. (2001) “Exchange rate regimes and economic performance”. IMF Staff Papers 47, 62-98. Levy-Yeyati, E. and Sturzenegger. F. (2003) “To float or to fix: evidence on the impact of exchange rate regimes on growth”. American Economic Review 93 (4), 1173-1193. Levy-Yeyati, E. and Sturzenegger. F. (2005) “Classifying exchange rate regimes: Deeds vs. words”. European Economic Review, Volume 49, Issue 6, August 2005, Pages 1603-1635. Levy-Yeyati, E. and Sturzenegger. F. (2016) “Classifying exchange rate regimes: 15 years later”. CID Faculty Working Paper No. 319, June 2016.


30

Exhibit 2 / An association between the cash use intensiveness and construction activity

The evolution in payment methods is the result of innovations that seek to meet the demand for more efficient interaction mechanisms for economic agents. At the global level, a large share of transactions still takes place in cash, the main causes of which is still cause for debate.

One of the objectives of the BCRA is to encourage the use of electronic means of payment and to make them accessible to users as an essential element for financial inclusion.26 In order to design the right policies and measures to ease and foster the use of electronic means of payment, it is important to understand the drivers behind the use of cash in Argentina. Next, we show the relation between cash use intensiveness and construction activity in the economy.

As is to be expected, due to transactional reasons, there is a positive association between the number of bills and coins in the hands of consumers in real terms and the size of the economy. However, this association is not stable.27 It has been found that the change in the intensiveness of the use of bills and coins might be accounted for, in part, by the evolution of construction activity relative to the economy as a whole.28 This may suggest that different economic activities are different in terms of their cash use intensiveness (see Figure 1).

26 See objectives and plans for the development of monetary, exchange rate, financial and credit policies for the year 2017 (http://www.bcra.gob.ar/Pdfs/Institucional/ObjetivosBCRA_2017.pdf. 27 We define cash use intensiveness as the ratio between total bills and coins in the hands of consumers and GDP at current prices. 28 Defined as the ratio between the estimator of construction activity and the Monthly Estimator of Economic Activity (EMAE)

Figure 1 | Ratio Banknotes and coins/GDP vs Ratio Construction /EMAE

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

50.0

52.5

55.0

57.5

60.0

62.5

65.0

67.5

70.0

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Banknotes and coins / GDP ratio

Construction / EMAE ratio (right axis)

Source: BCRA and INDEC


31

In order to determine whether the series are correlated, it is important to rule out a common underlying trend. To do so, the linear trend is found for both series, and their cyclical components are analyzed. For the period 2004-2016, the correlation between both series is positive, except for the sub-period 2011-2015. In the sub-periods before (Jan-2004 to Oct-2011) and after exchange rate restrictions (Dec-2015 to Jul-2017), the correlation is positive. In contrast, while the restrictions were in place, cash demand rose significantly and turned the correlation between the two variables negative (see Table 1).

To test the correlation, a regression analysis was carried out between the cyclical components of both variables. Moreover, a dummy variable was included for the foreign exchange controls (cepo cambiario) period, which enhanced the estimation fit. The results suggest that the coefficient associated with the evolution of construction activity relative to aggregate activity is positive and statistically significant to account for the behavior of cash use intensiveness.

As from the normalization of the exchange rate regime (December 2015), the correlation between both becomes significant, and construction growth relative to economic activity is one of the factors that explains the rise in cash use intensiveness during 2016 and 2017.

Table 1 | Correlation between cycles of banknotes and coins over GDP and construction over EMAE (2004-2017)

2004‐2017 2004‐2011 2011‐2015 2016‐2017

Cycle (Banknotes and coins) vs Cycle (Construction) 0.409 0.438 ‐0.283 0.559



32

Exhibit 3 / Public Private Partnership (PPP) Historically, infrastructure projects in an economy —such as highways, bridges, airports, and schools— have been considered as public goods and, as such, have been built by Governments, financed through taxes and managed by public bodies. However, as from the late 1980s, several countries began using Public Private Partnership (PPP) in some of these developments. PPP can be defined as an agreement by which the government hires a private enterprise to build or improve infrastructure projects, and later maintain them and operate them for an extended period of time in exchange of a fee during the term of the agreement. In general terms, the concession holder is compensated with a combination of income from the users (a toll booth on the motorway) and/or Government transfers (public hospitals). In all the cases, at the end of the agreement, the asset goes back to the State.29 Infrastructure projects such as highways, bridges, tunnels, and harbors are big investments which require a large amount of capital, and, once they are built, they also need to be maintained and operated. Therefore, the process through which projects are selected, designed, operated, and maintained is essential. One of the main barriers to growth and development in Latin America has been the lack of infrastructure which is usually reflected in bottlenecks and several inefficiencies, which creates obstacles to investment, which, in turn, restricts growth even more.30 The evolution of quality in infrastructure31 in the last decade in the main economies of Latin America32 has shown a heterogeneous behavior by country and by component (see Figure 1).

29 Engel, Fischer, and Galetovic. The Economics of Public-Private Partner-ships: A Basic Guide. Cambridge University Press, 2014. 30 Garcia-Escribano, Góes, and Karpowicz, 2015, “Filling the Gap: Infrastructure Investment in Brazil,” IMF Working Paper 15/180. 31 The World Economic Forum generates the quality of infrastructure indicator. This indicator ranges between one (1) —very poor quality— to seven (7) —the highest score, meaning the infrastructure has good development and efficiency in accordance with international standards. 32 Argentina, Brazil, Chile, Colombia, Mexico, and Peru account for 84 percent of the region's GDP. WEO, April 2017.

Figure 1 | Infrastructure quality indicators

‐6%

‐4%

‐2%

0%

2%

4%

6%

8%

Argentina Brazil Chile Colombia Mexico Peru

Overall infrastructure

Electricity supply

Roads

Railroad

Air transport

Port

Source: World Economic Forum


33

Recognizing that investment in infrastructure increases productivity of all production factors, improves competitiveness, and increases the export capacity, many countries in Latin America have focused their attention on investment in infrastructure in order to strengthen their long term productive capacity through Public Private Partnership agreements33 (see Figure 2).

In our country, the approval of the Public Private Partnership Act34 enabled PPP agreements as a tool for the private sector to finance, build, operate, and/or maintain a public good or service, while the Government, or the Government together with the private sector, repay these capital investments and operation and maintenance costs in the long term against a service delivery. PPPs are an alternative to the classical systems for public work contracting, aiming at developing projects in the areas of Energy and Mining; Transport, Communication, and Technology; Water, Sanitation, and Dwelling; and Education, Health, and Justice35. A key difference when comparing the traditional public investment model with PPPs is risk allocation faced by taxpayers represented by the public sector (see Figure 3). In the traditional scheme to generate infrastructure through public work, project funding is based on the Government's financing cost, while in PPPs, the funding cost reflects the project's risk assessment by the private sector and the credit rating of the banks involved. Even in the hypothetical case in which the cost could be higher in PPPs than the traditional model, taxpayers do not have to face the commercial risks, such as project construction and maintenance risks, thus changing the risk/reward ratio. As a consequence, we could say that, although financing infrastructure through PPPs allows to keep-off-balance-sheet account of public investment, its main benefit is actually its capacity to diversify the parties' risks, take advantage of innovations in the private sector, and thus bring more efficiency to the use of resources.

33 There are four key infrastructure types for the region for which PPPs are used: transport, energy, telecommunications, and water supply and sewerage. Private Participation in Infrastructure (PPI), Workl Bank, 2016. 34 Act 27.328. 35 Based on data from the Ministry of Finances' Public Private Partnership Unit, the first 52 projects anticipate an investment by the private sector of USD 21 billion. https://www.minfinanzas.gob.ar/uppp/index.php.

Figure 2 | PPP projects distribution by region (2007-2016)

17% 24%

24%

23%

26% 23%43%

48% 45%42%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

East Asia and Pacific Europe and Central AsiaLatin America and the Caribbean Middle East and North AfricaSouth Asia

Source: World Bank


34

These operations do face at least two challenges, according to the literature specialized in execution and implementation of PPPs in the region. Firstly, the existence of contingent liabilities resulting from a poor design of the contract with the private sector may cause the latter to eventually incur losses which may force it to carry out a restructuring and the public sector to assume their debts and liabilities against third parties.36 Secondly, if the PPP-related law is inconsistent, there may be situations in which contract renegotiation may undermine the gains in efficiency of PPPs and the return on such investment. Due to the high occurrence of contract renegotiation observed in several countries of the region, some countries, such as Chile, have introduced reforms to limit contract renegotiation.37

36 For more information about this, see Ehrhardt and Irwin, 2004; Cebotari et al, 2008; Bloomgarden and Blumenfeld, 2013. 37 For more information about this, see Bitran, Eduardo, Sebastan Nieto-Parra, and Juan Sebastan Robledo, 2013, “Opening the Black Box of Contract Renegotiations: An Analysis of Road Concessions in Chile, Colombia and Peru,” OECD Working Paper No. 317 (Paris: Organisation for Economic Co-operation and Development).

Figure 3 | Traditional (public) investment vs. PPP (private) investment

State

Banks

Construction

company

Operating

company

PPP

State

Banks

Construction

company

Operating

company

Traditional investment Private investment

Long term servicecontract

Investmentcontracts

Operationcontracts

Constructioncontract

Constructioncontract

Operationcontracts

Investmentcontracts

Source: Managing Fiscal Risks in PPPs, current issues in fiscal reform in Central Europe


35

4. Prices During the third quarter, inflation slowed down slightly relative to previous quarters, with a 1.7 percent monthly increase. The core component increased at a monthly rate of 1.6 percent: 0.1 percentage points below that of the previous quarter. Core inflation was the lowest of the last few years, though it remains above the monetary authority’s target level and shows a certain degree of persistence. During the third quarter, inflation moved at a year-on-year rate of 22.7 percent, 1.7 percentage points below that of the previous quarter. Inflation expectations suggest that the disinflation process will continue in the medium term. The projections of the analysts included in the Market Expectations Survey (REM) foresee a gradual moderation. While market expectations continue to move above the inflation targets set by the BCRA, they are below the levels seen in the last eight years.

4.1 Inflation Continued to Decelerate During the third quarter of the year, retail prices continued to slow down, though at rates above the ones targeted by the BCRA for this period. The CPI38 recorded an average change of 1.7 percent (a year-on-year rate of 22.1 percent), 0.1 percentage points below that of the second quarter (see Figure 4.1). The behavior of core inflation39 was similar to that of headline inflation, with a 1.6 percent increase in the third quarter (0.1 percentage points lower than the previous period; see Figure 4.2).

38 Nation-wide price index prepared by INDEC. 39 Accounting for approximately 70 percent of the basket.

Figure 4.1 | CPI. Headline

2.0 2.0

1.9

2.3

2.0

1.9

2.1

1.8 1.8

1.7

1.7

1.8

2.0

1.61.7 1.7

1.7

1.5

1.2

1.5 1.5

0.0

0.5

1.0

1.5

2.0

2.5



m.o.m. avg. % chg. Q1‐17 Q2‐17 Q3‐17

Source: INDEC


36

During the first nine months of the year, retails prices increased 17.6 percent in overall terms and 16.1 percent in terms of core inflation. As projected, the year-on-year change of the CPI increased in August and September, due to the smaller comparison basis caused by the temporary suspension of the gas fee increase during these months in 2016. In turn, core inflation, which excludes regulated prices, maintained a decreasing path in the year-on-year comparison.

This slower increase in the headline level took place while the process of updating the relative prices of regulated items continued. So far this year, this set increased 23.2 percent, a rate above that of core inflation. Seasonal goods and services grew 16.2 percent during the year, in line with the increase of core inflation. Core inflation maintained a certain degree of persistence in its monthly growth rate at the national level. This behavior mainly reflects what happened in the Greater Buenos Aires Area and the Pampeana region, which account for approximately 80 percent of the index. Remaining regions showed a deceleration, which is particularly marked in the Northeast region. The measure in the City of Buenos Aires and other core inflation measures prepared by the BCRA40 based on disaggregated information from that index also show a stable rate of growth relative to the last quarters. In spite of the persistence shown by core inflation, it is at the lowest levels of the last few years (see Figure 4.3). Data on the first days of October taken from the high-frequency PriceStats index appear to suggest that inflation will slow down (1.2 percent, 30 days moving average).

40 The method used by the statistical institutes is that of excluding components. Having said that, it is also possible to compute other statistical measures by using econometric techniques (such as main components and truncated means; see Exhibit 5 of the July, 2016 edition of the IPOM).

Figure 4.2 | CPI. Core

1.7

1.7 1.7

1.7 1.8

1.7 1.7

1.7 1.8

1.6

1.5

1.9

1.8

1.7

1.6 1.7

1.6

1.5

1.3

1.5

1.5

0.0

0.4

0.8

1.2

1.6

2.0



m.o.m. % avg. chg. Q1‐17 Q2‐17 Q3‐17

1.74

Source: INDEC

Q4‐16 (GBA)


37

In order to analyze the behavior of core inflation by goods and services, the City of Buenos Aires’ CPI was used: not enough disaggregated information is available in the CPI prepared by INDEC41. During the third quarter of the year, core component goods continued to grow at a lower rate than private services42. Good’s inflation maintained a rate similar to that of the first half of the year, while private service inflation continued on its deceleration trend (see Figure 4.4). This behavior of services is consistent with the rate of increase of nominal wages, in a context of growth in economic activity (see Subsection 4.2).

41 The dynamic of good and service prices in both measures is similar, both in monthly terms and in terms of the cumulative increase in the year. 42 Services in the core component do not include regulated and seasonal services.

Figure 4.3 | CPI. Core

Figure 4.4 | Core inflation trend for goods and private services. City of Buenos Aires

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5Dec‐12

Mar‐13

Jun‐13

Sep‐13

Dec‐13

Mar‐14

Jun‐14

Sep‐14

Dec‐14

Mar‐15

Jun‐15

Sep‐15

Dec‐15

Mar‐16

Jun‐16

Sep‐16

Dec‐16

Mar‐17

Jun‐17

Sep‐17

%

3‐month m.a.

6‐month m.a.

Note: The serie corresponds to the CPI of National coverage of INDEC from Dec‐16, linked with the Greater Buenos Aires CPI up to Apr‐16 and before with the City of Buenos Aires CPISource: INDEC and Statistical Office of the City of Buenos Aires

1.7

1.4

1.9

1.3

1.7

2.1

2.5

2.9

3.3

m.o.m. % chg.

Core

Goods

Private services

Note: Trend using a Hodrick‐Prescott filter with λ=100 applied over the City of Buenos Aires CPI Core serie (excludes health insurance and formal education). Considering that the HP filter is symmetrical, the serie was forecasted up to Dec‐16 uisng an ARIMA model. Source: Statistical Office of the City of Buenos Aires


38

The adoption of an inflation targeting regime with a flee-floating exchange rate was aimed at achieving disinflation in the economy without using the exchange rate as a nominal anchor (see the section on Monetary Policy). The correlation between the nominal exchange rate and core inflation since the establishment of the regime has been negative (-0.33), while in 2011–2015, the ratio was positive (0.43). This decoupling between variables can also be seen in the relative volatility between the nominal exchange rate and inflation, a ratio which increased significantly with the new regime (see Figure 4.5).

Wholesale prices grew at an average monthly rate of 1.8 percent during the quarter. In year-on-year terms, these prices grew 16.3 percent: 7.5 percentage points lower than the year-on-year rate of increase in consumer prices (see Figure 4.6).

Figure 4.5 | Prices and nominal exchange rate

Figure 4.6 | Consumer and wholesale prices

‐0.3‐0.25‐0.2

‐0.15‐0.1

‐0.050

0.050.1

0.150.2

PriceStats

Nominal multilateral exchange rate (NMER)*

Nominal exchange rate against US$**

log points

Note: Logarithm of the daily series with base on the average Jan‐16 to Sep‐17. * Geometric mean weighted by the trade flows (excludes primary products and fuel and energy) of the nominal bilateral exchange rate with: Brazil, Canada, Chile, United States, Mexico, Uruguay, China, India, Japan, United Kingdom, Switzerland and the Euro zone. ** For the US dollar the BNA price was considered. Source: State Street' PriceStats Aggregate Inflation Series, INDEC and Datastream

‐4

‐2

0

2

4

6

8

10

12

Jul‐12

Sep‐12

Nov‐12

Jan‐13

Mar‐13

May‐13

Jul‐13

Sep‐13

Nov‐13

Jan‐14

Mar‐14

May‐14

Jul‐14

Sep‐14

Nov‐14

Jan‐15

Mar‐15

May‐15

Jul‐15

Sep‐15

Nov‐15

Jan‐16

Mar‐16

May‐16

Jul‐16

Sep‐16

Nov‐16

Jan‐17

Mar‐17

May‐17

Jul‐17

Sep‐17

m.o.m. % chg.

CPI. Headline*

Nominal exchange rate against US$

* Excludes health insurance and formal education. The price serie corresponds to the CPI of national coverage from the INDEC up to Dec‐16, before the Greater Buenos Aires CPI up to apr‐16 and before the City of Buenos Aires CPI.Source: INDEC, Statistical Office of the City of Buenos Aires and BCRA

23.822.3

18.7

16.3 15.8 15.4

0

5

10

15

20

25

CPI. Headline CPI. Core CPI. Goods IPIM IPIB IPP

y.o.y. % chg.

Note: The CPI series correspond to the CPI of National coverage of INDEC from Dec‐16, linked before with the Greater Buenos Aires CPI.Source: INDEC


39

By disaggregating the CPI it is possible to see that, in cumulative terms, the groups associated to total utilities (regulated and non-regulated) are the ones that increased the most. In the case of regulated services, it can be explained by the process by which fees were updated after several years without changes. The groups with a greater share of goods contributed to ease inflation pressures. The most significant ones were those favored by the context of greater trade openness, such as equipment and home maintenance, a group which includes the price evolution of home appliances and electronics (see Figure 4.7).

4.2 Nominal Wages Grew at a Slower Pace During the third quarter, nominal wages had increased faster than inflation. For the last part of the year, a deceleration in the rate of growth of labor costs is expected, given the structure of wage negotiation agreements (see Figure 4.8).

Figure 4.7 | National CPI. Opening by division

Figure 4.8 | Salaries of the private sector (3-month m. a.)

17.6

18.1

16.4

15.5

12.3

11.8

30.0

29.3

24.3

21.9

19.5

16.2

12.0

0

5

10

15

20

25

30

%

Headline

Great share of goods

Great share of services

Source: INDEC

24

28

32

36

Dec‐13 Dec‐14 Dec‐15 Dec‐16 Dec‐17

y.o.y. % chg.

Ministry of Labor

23 labor unions. Forecast*

* The forecast of the 23 labor unions is calculated by weightening the salary of each labor union considering the number of affiliates of each labor union.Source: Ministry of Labor


40

Most adjustment clauses would not be triggered, as inflation will most likely be below the agreed wage increases (see Table 4.1). If our expectations for nominal wages hold true, the year will end with an average increase in real wages of approximately 4 percent.

Table 4.1 | Wage agreements

Agreement period

of validity

% of wage raise

2017/2018

Allows for

revisiones

share of the

private formal

employment (%)

Oilers Fed. Aceitera Apr‐17/Mar‐18 31.6 0.8%

Food Processing STIA Apr‐17/Mar‐18 30.0 review instance 5.8%

Banking Bancaria Jan‐17/Dec‐17 19.5 trigger clause 2.6%

Footwear UTICRA Jun‐17/May‐18 22.5 0.6%

Trucking FEDCAM Jul‐17/Jun‐18 24.7 1.7%

Commerce FAECyS Apr‐17/Mar‐18 20.0 review instance 18.7%

Construction UOCRA Apr‐17/Mar‐18 21.0 review instance 6.8%

Janitors SUTERH May‐17/Apr‐18 21.0automatic

adjustment0.4%

Restaurants UTHGRA Jun‐17/May‐18 24.0 review instance 4.3%

Textile SOIVA Apr‐17/Mar‐18 25.0 review instance 0.7%

Metalworking UOM Apr‐17/Mar‐18 22.0 2.0%

Plastics UOYEP Jun‐17/May‐18 21.0 1.1%

Chemical and Petrochemical FESTIQyPRA May‐17/Apr‐18 23.0 1.7%

Health FATSA Jun‐17/May‐18 23.0 trigger clause 5.1%

Buses UTA Apr‐17/Mar‐18 21.0 review instance 5.3%

Total 57.6%

Source: Press publications, unions information and Bank estimates

Main unions

Annual agreements


41

4.3 Disinflation would continue in the Last Part of the Year Analysts expect the disinflation process to continue, albeit gradually, in the next few months, according to the expectations captured by the Market Expectations Survey. For the last quarter of the year, they project an average monthly inflation rate of 1.4 percent (a year-on-year rate of 18 percent), below that recorded in the first part of the year. In year-on-year terms, expectations hovered around a year-on-year rate of 22 percent for December, 2017, and 16.9 percent for the following twelve months (see Figure 4.9). While market projections remain above the inflation rates set by the BCRA, they are below the values seen in the last eight years.

Figure 4.9 | Inflation expectations

22.0

16.9 15.812.1 11.012

17

10

5

0

5

10

15

20

25

30

35

40

45

50

Jun‐16

Aug‐16

Oct‐16

Dec‐16

Feb‐17

Apr‐17

Jun‐17

Aug‐17

Oct‐17

Dec‐17

Feb‐18

Apr‐18

Jun‐18

Aug‐18

Oct‐18

Dec‐18

Feb‐19

Apr‐19

Jun‐19

Aug‐19

Oct‐19

Dec‐19

Inflation y.o.y.

REM inflation expectations

Inflation target

y.o.y. % chg.

Note: IPC series correspond to CPI of national coverage from dec‐16, linked with the Greater Buenos Aires CPI up to apr‐16 and backward with the CPI National weighted (weighted average by expenditure of the the CPIs of the City of Buenos Aires, Córdoba and San Luis). Source: INDEC, Statistical Office of the

City of Buenos Aires and Market Expectations Survey (REM‐ BCRA) as for Sep‐17


42

Exhibit 4 / Mixed-Frequency Model Forecasts The Central Bank is constantly monitoring low- and high-frequency indicators of price inflation. This exhibit explains the statistical methodology to infer the evolution of low-frequency indicators based on real-time data. Provincial and “private” price indices are useful indicators for that purpose; in particular, the “resto IPCBA” price index, prepared by the General Directorate of Statistics and Census of the Government of Autonomous City of Buenos Aires, as well as the index prepared by the company PriceStats, in collaboration with State Street Global Markets.50 The former is issued monthly and aims at providing a view of the trend of the inflation rate by excluding regulated prices and prices with a marked seasonal component, while the latter provides a daily indicator of the evolution of prices based on the compilation of prices from the web sites of several online retailers in Argentina and their aggregation imitating the methodology of a standard consumer price index.

As can be observed in Figure 1, the monthly aggregation of the daily State Street PriceStats index is a good approximation for the monthly “resto IPCBA” inflation rate, though slightly more volatile. The issue is whether it is possible to combine both indices in a model that makes it possible to predict the “resto IPCBA” inflation rate. Ghysels et al. (2004)51 propose, in their most simplified version, a simple regression equation to address this issue,

where represents the monthly core inflation rate, “resto IPCBA” (low frequency), and , the daily rate of inflation from State Street PriceStats (high frequency), both approximated through logarithmic

50 The data are partially published at InflacionVerdadera.com. 51 Ghysels E., Santa-Clara P., Valkanov R. (2004). “The Midas touch: mixed data sampling regression models”. Working Paper 2004s-20. CIRANO.

Figure 1 | Comparison between resto IPCBA and aggregated PriceStats

‐1

0

1

2

3

4

5

6

7

Aug‐12 Jun‐13 Apr‐14 Feb‐15 Dec‐15 Oct‐16

m.o.m. % chg.

resto IPCBA

State Street PriceStats

Source: Central Bank of Argentina, Department of Statistics and Censuses of the Autonomous City of Buenos Aires and State Street’ PriceStats Aggregate Inflation Series


43

differences; is a constant; is the number of times the high-frequency variable is observed52, each represents the weight of each day in the month53; and is the residual term. This methodology, known as MIDAS (Mixed Data Sampling Regressions), makes it possible to define a relatively simple model to combine high- and low-frequency information. Consequently, it also allows intra-period estimations, with a slight modification to the specification of the previous equation, which enables us to compute a different forecast for each day of the month as more information becomes available. In Figure 2, we analyze the performance of these models for the period going from August 2015 through July 2017. Two particular features can be highlighted: i) as the inflation rate falls, the forecast become more and more accurate, and ii) as the month progresses, while there is some volatility, the quality of predictions increases on average.

Analyzing ii) in more detail, it is interesting to compare the accuracy of these models with other simple models, such as an autoregressive model, using only the low-frequency “resto IPCBA” index or the moving average provided by InflacionVerdadera.com, using only the high-frequency index of State Street PriceStats. Figure 3 shows the evolution of the average accuracy of the forecasts, considering the period between August 2016 through July 2017. The forecasts’ accuracy is considered in terms of the square root of the mean square error of the forecasts; thus, a lower value implies on average a more accurate forecast. 52 Assumed to be a fixed number; thus, observations are discarded for the days 29, 30 and 31 of the relevant months. 53 In order to eliminate the resulting parameter proliferation, a polynomial restriction needs to be applied, so that each coefficient is a function of its position within the month and of a fixed number of parameters to be estimated.

Figure 2 | Evolution of the forecast for the current month

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

08‐01‐2015 12‐01‐2015 04‐01‐2016 08‐01‐2016 12‐01‐2016 04‐01‐2017

m.o.m. % chg.

confidence lower band (80%)

MIDAS‐ADL

Confidence upper band (80%)

Observed



44

In conclusion, mixed-frequency models achieve better results than estimators that consider a single frequency, either high (only State Street PriceStats) or low (only rest CPIBA). Additionally, as the number of observations of the National CPI, recently launched by the new INDEC administration, increases, it will be possible to use these models to predict that index.

Figure 3 | Evolution of the average precision of the forecasts through the month

0.40

0.45

0.50

0.55

0.60

0.65

0.70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

root mean squared error

InflaciónVerdadera.com

AR(1)

MIDAS‐ADL



45

5. Monetary Policy The primary monetary policy goal is to achieve a low and stable level of inflation. To that effect, the BCRA established a decreasing trend of inflation targets: between 12 percent and 17 percent for 2017, 10 percent ± 2 percent for 2018, and 5 percent ± 1.5 percent starting in 2019; and chose the mid-band of the 7-day repo rates corridor as the main policy instrument. In the third quarter of the year, retail inflation continued to show a marginally decreasing trend, with a slight fall in the average monthly inflation rate, compared to that of the previous quarter (see Figure 4.1). However, core inflation continues to be persistent, as price increases remained above the level sought by the BCRA, which implies a year-end inflation consistent with the 10 percent ± 2 percent target of 2018 (see Figure 4.2). At the same time, inflation expectations increased slightly over the quarter, which project a 12 percent year-on-year inflation will in the third quarter of 2019 (see Figure 4.9). In this context, the monetary authority kept the policy rate stable at 26.25 percent over the quarter, while the real interest rate reflected a more restrictive stance, due to the decreasing trend shown by the expected monthly inflation rate. Moreover, the BCRA continued its active operations in the LEBAC secondary market, with the goal of reinforcing the transmission of this more restrictive stance to the remaining market interest rates, which led to increases in these instruments’ interest rates over the quarter.

The BCRA will keep a clear anti-inflation bias in order to ensure that the disinflation process continues towards an end-2017 inflation rate consistent with the 10 percent ± 2 percent target for 2018. Figure 5.1 shows different monthly average inflation rate scenarios for the last quarter of the year, with their respective paths for 2018, consistent with the year-on-year 10% target for December 2018.

Figure 5.1 | Inflation scenarios consistent with the 10% y.o.y. target at December 2018

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%

Q4‐17 Q1‐18 Q2‐18 Q3‐18 Q4‐18

IV17 ‐ Scenario 1.4 IV17 ‐ Scenario 1.3 IV17 ‐ Scenario 1.2

Annualized last month:

6.8%7.2%

7.6%

Source: BCRA


46

5.1 BCRA Monetary Policy during the third quarter The slowdown of inflation in the second quarter of 2016 led to an easing of the monetary policy, which, coupled with the increases in regulated prices, resulted in monthly rates above the levels compatible with the path set forth by the monetary authority for the February-April period of this year. The BCRA reacted by increasing its monetary policy rate, the mid-band of the 7-days repo rates corridor, by 150 basis points on April 11, to a yearly 26.25 percent, and restricting liquidity conditions in the LEBAC secondary market, which caused an increase in the interest rates of those instruments. These contractive monetary policy measures launched a deceleration of inflation. During the third quarter of the year, retail inflation continued to show a marginally-decreasing trend, with a slight fall in the average monthly inflation rate, compared to the previous quarter (see Figure 4.1). However, core inflation continues to be persistent, as price increases remained above the level sought by the BCRA, which aims for a year-end inflation rate consistent with the target of 10 percent ± 2 percent for 2018 (see Figure 4.2). At the same time, inflation expectations increased slightly over the quarter, which project that the year-on-year inflation rate will reach the 12 percent level in the third quarter of 2019 (see Figure 4.9). In this context, the monetary authority kept its policy rate stable at a yearly 26.25 percent over the quarter, while the real interest rate reflected a more restrictive stance, due to the decreasing trend displayed by expected monthly inflation rates (see Figure 5.2).47

As a way of supplementing the policy rate management, the BCRA has continued its active operation in the LEBAC secondary market, with the goal of reinforcing the transmission of this more restrictive stance to the rest of the market’s interest rates. Thus, in the third quarter, the BCRA continued to restrict the monetary market liquidity conditions, through operations in the LEBAC secondary market (open market operations). Between July and September, the BCRA sold LEBAC in the secondary market for a total NV of

47 With the goal of assessing the character of the monetary policy, it is convenient to consider the price indices which measure core inflation. These measures are a more accurate indicator of underlying inflation. To compute real rates taking into account core inflation expectations reduces the fluctuations produced by changes in regulated and seasonal prices.

Figure 5.2 | Nominal and real monetary policy rate

0

5

10

15

20

25

30

35

40

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

May‐16 Jul‐16 Sep‐16 Nov‐16 Jan‐17 Mar‐17 May‐17 Jul‐17 Sep‐17 Nov‐17 Jan‐18

APR, %%

Monthly effective rate (left axis); annual nominal rate (right axis)

monthly expected inflation ‐ Core (GBA and National)

Monthly effective rate ‐ Core (GBA and National)

Monthly expected inflation ‐ National

Monthly real effective rate ‐ National

REMExpectations

Source: BCRA

35‐day LEBAC 7‐day Repo corridor


47

$410.8 billion. Thus, open market operations accounted for 21 percent of the total transactions —quarterly average— in the LEBAC secondary market (see Figure 5.3).

Over the quarter, together with the restriction of liquidity conditions, the monetary authority attempted to modify the slope of the LEBAC yield curve. Thus, by the end of August, the yield curve observed in the secondary market began showing a flatter shape, and, at the end of September, adopted a slightly positive slope (see Figure 5.4). This implied a 1.7 percentage point increase in shorter maturity securities and a 3.6 percentage point increase in longer maturity securities between the end of June and the end of September. This change in the curve led to a gradual lengthening of the average term of the outstanding LEBAC stock, which went from an average 43 days in June, to an average 75 days in September.

Figure 5.3 | Central Bank interventions in the LEBAC secondary market

Figure 5.4 | Secondary market LEBAC yield curve

22

43

5 7

0 1

7

5

11

13

87 8

2

4

1 0 0

14 14

20

12

1614

10

0

5

10

15

20

25

0

10

20

30

40

50

60

70

80

90

100

Jul‐15 Nov‐15 Mar‐16 Jul‐16 Nov‐16 Mar‐17 Jul‐17

Other

Central Bank interventions

Central Bank secondary market operations / LEBAC stock ratio%

Source: BCRA

%

23.5

24.0

24.5

25.0

25.5

26.0

26.5

27.0

27.5

28.0

0 30 60 90 120 150 180 210 240 270 300

29‐Sep‐17

31‐Aug‐17

30‐Jun‐17

APR; %

daysSource: BCRA


48

5.2 Transmission of the Policy Rate to the Remaining Market Interest Rates

The money market interest rates continued to increase in the third quarter of the year. The restrictive liquidity conditions in the market caused interest rates to leave the low end of the band and approach the center, in line with the monetary authority’s plans. In this sense, the 1-day interbank call rate increased 1.7 percentage points between June and September, and reached a monthly average of 26.4 percent per year (see Figure 5.5). The repo rates corridor established by the BCRA contributes to keep the volatility of the interbank market interest rates in check: the reverse repo interest rate works as a lower bound for the interbank market rates, while the repurchase agreement interest rates work as a ceiling. After the change in the monetary policy instrument, facilities began to be used more frequently by financial entities, particularly repurchase agreements, which were seldom used before. Thus, as expected, the rate movement towards the mid-band took place together with a sustained reduction in the stock of reverse repo over the quarter and an increase in repurchase agreements, particularly in September (see Figure 5.5).

In turn, deposit interest rates, which in the previous quarter had been relatively stable, started increasing due to the restrictive liquidity conditions. In the wholesale segment, the private bank BADLAR increased 1.5 percentage points and reached a monthly average of 21.3 percent in September. In spite of that, they remain lagged comparing the funding cost of wholesale deposits adjusted by reserve requirements with the 35-day LEBAC rate, with an average 2.4 percentage point spread in the quarter. In the retail segment, the increase in the interest rate of fixed term deposits was slightly lower, 1 percentage point, and the rate closed September with a 17.9 percent monthly average (see Figure 5.6).

Figure 5.5 | Overnight repo rate corridor and interbank interest rate

0

50,000

100,000

150,000

200,000

250,000

20.0

21.0

22.0

23.0

24.0

25.0

26.0

27.0

28.0

29.0

Jan‐02‐17

Jan‐16‐17

Jan‐30‐17

Feb‐13‐17

Feb‐27‐17

Mar‐13‐17

Mar‐27‐17

Apr‐10

‐17

Apr‐24

‐17

May‐08‐17

May‐22‐17

Jun‐05‐17

Jun‐19‐17

Jul‐03‐17

Jul‐17‐17

Jul‐31‐17

Aug‐14‐17

Aug‐28‐17

Sep‐11‐17

Sep‐25‐17

million $%, APR Reverse repos (right axis) Repos (right axis)

Call 1‐day repo corridor

Source: BCRA


49

The increase in bank borrowing interest rates took place in a context of credit expansion and liquidity reduction in financial entities. Indeed, the broad liquidity of the whole financial system, which includes cash in banks, current account deposits with the BCRA, net repo and LEBAC, went from 44.7 percent in June to 40.2 percent in September (see Figure 5.7), with net repo explaining most of the fall.

Figure 5.6 | LEBAC and deposit rates

Figure 5.7 | Financial system liquidity ratios in pesos

14

18

22

26

30

34

38

42


APR; %

BADLAR private banks

BADLAR private banks. Corrected with reserve requirements ratio

Time deposits ‐ up to $99.999

35‐day LEBAC ‐ Secondary market

Source: BCRA

13.2 13.1 13.1 13.3

4.1 4.3 4.0 4.0

4.8 2.7 1.4 0.7

22.522.4

22.7 22.2

43.4 44.2 44.4 44.242.5

44.8 45.4 45.4 45.3 44.742.5 41.2 40.2

0

5

10

15

20

25

30

35

40

45

50

Sep‐16 Oct‐16 Nov‐16 Dec‐16 Jan‐17 Feb‐17 Mar‐17 Apr‐17 May‐17 Jun‐17 Jul‐17 Aug‐17 Sep‐17

% of deposits

Current account at Central Bank ($)

Bills and coins

Net repos

LEBAC and NOBAC

Total liquidity

Source: BCRA


50

At the same time, peso-denominated loans to the private sector accelerated their expansion rate in the third quarter, with an average 1.8 percent monthly increase in real terms (seasonally adjusted), relative to the monthly 1.2 percent increase from the previous quarter, which took the loan-GDP ratio from 10.1 percent in June to 10.4 percent in September, a level which is still low in historical terms (see Figure 5.8). This expansion of peso-denominated financing was led by mortgage loans, within which those granted in UVA accounted for most of the behavior, followed by document discounting and collateral loans. In turn, foreign-currency-denominated loans were even more dynamic during the quarter, with an average real monthly seasonally-adjusted growth of 6.4 percent, and going from 1.9 percent of the GDP to 2.3 percent (see Figure 5.8). The continuation of the credit expansion process in a context of decreasing liquidity from banks will keep reinforcing the transmission mechanism of the policy rate to the rest of the banks’ borrowing rates.

Lending interest rates continued to show a mixed behavior during the quarter. Considering monthly average interest rates of private sector loans, in the case of corporate financing, the rates for advances in current accounts and signature loans increased 0.6 percentage points and 0.5 percentage points, respectively, while the rates for discounted documents remained virtually stable between June and September. As regards credit associated with consumption, the cost of personal loans increased 1.3 percentage points in the same period, whereas credit card rates decreased slightly. Finally, the interest rate of secured loans fell 0.3 percentage points in the quarter (see Figure 5.9).

Figure 5.8 | Financial system loans to private sector (% of GDP)

9.0

9.5

10.0

10.5

11.0

11.5

12.0

12.5

13.0

Sep‐14 Sep‐15 Sep‐16 Sep‐17

% of GDP

Pesos and US dollars

Pesos

Source: BCRA


51

5.3 Exchange Flexibility and International Reserve Buildup

The BCRA implemented in December 2015 a flexible exchange regime, of the type commonly used in countries with inflation targeting regimes, that enables the economy to better absorb external shocks (see Exhibit 1 / Floating exchange rate and current account volatility). At the same time, the BCRA intervened in the exchange market purchasing currency, with the goal of achieving a level of international reserves similar to that of other countries in the region that also use an inflation targeting regime and a floating exchange rate. This strategy is based on a precautionary demand of foreign currency which can later be used to prevent disruptive volatilities in the exchange rate, but whose purpose is not to set its level. During 2016, several episodes made it possible to see how this scheme works during adverse shocks: the uncertainty associated with the Brexit and the results of the US election, whereby the peso depreciated vis-à-vis the dollar. In May this year, the political situation in Brazil had a similar impact on the exchange market, which lasted until early August, because of the expectations regarding the results of the Argentine PASO (primary elections). The domestic currency depreciated approximately 15 percent relative to the dollar since mid-May until August 11 (the Friday before the election). As with the 2016 exchange volatility episodes, the dollar appreciation did not have a significant effect on the quarter’s retail inflation (see Figure 4.5). This behavior is a favorable sign of the credibility of the monetary policy, which is critical for exchange rate flexibility to be an efficient tool for shock absorption. At the same time, in the last few months, it became evident that the strategy of accumulating international reserves is a useful tool to prevent unnecessary uncertainty in the exchange market. In the face of the sustained increase in the exchange rate in the weeks before the election, when the market’s liquidity had recorded a sharp reduction, the BCRA intervened to moderate an exchange volatility that was considered excessive. Thus, between July 28 and August 11, the BCRA sold international reserves on seven occasions, totaling US$1,837 million (an average of US$262 million per intervention). The exchange rate vis-à-vis the dollar abandoned its growing trend before the primaries, and, after the election, fell 2% until late September (see Figure 5.10).

Figure 5.9 | LEBAC and lending rates

30

35

40

45

50

19

24

29

34

39

44


Discounted notes 90‐days ‐ Private Banks

35‐days LEBAC ‐ Secondary market

Overdrafts up to 7‐days +$10 M ‐ Private Banks

Personal loans (right axis)

APR; %

Source: BCRA

APR; %


52

In spite of these interventions, purchases of foreign currency to the National Treasury carried out during the quarter made it possible for international reserves to grow US$2,242 million since late June, reaching US$50,237 million by the end of September. This level represents 8 percent of GDP, that is, 4.4 percentage points of the GDP recovery since the November 2015 low. Since April 18, when the BCRA announced its intention to increase the international reserve ratio to 15 percent of GDP, net purchases of foreign currency totaled approximately US$7 billion (see Figure 5.11).48

48 This is a secondary goal, that is, it is subordinated to that of achieving a low and stable inflation rate, and has no defined chronogram. International reserve accumulation is a usual strategy in many emerging economies, based on a precautionary demand of foreign currency, aimed at preventing disruptive volatilities in the exchange rate (see Exhibit 3 of the April, 2017, IPOM: “Strengthening the BCRA balance sheet: the experience in other emerging economies”).

Figure 5.10 | BCRA purchases and sales on the exchange market

Figure 5.11 | BCRA purchases and sales on the exchange market

12.5

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18.5

‐750

‐250

250

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Sep‐17

$/US$million US$ Purchases (+) / Sales (‐) to the private sector and others

Purchases (+) / sales (‐) to the National Treasury

Exchange rate (right axis)

Source: BCRA

‐2,000

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0

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2,000

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4,000

Apr‐17* May‐17 Jun‐17 Jul‐17 Aug‐17 Sep‐17 Oct‐17

million US$

National Treasury

Private sector and other

TotalReserves purchase

announcement Brazil**

*Since April, 18th. **Since May, 18th.Source: BCRA


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The counterpart of foreign currency accumulation is the issuance of bills and net reverse repo aimed at sterilizing the monetary expansion caused by the BCRA’s dollar purchases. These sterilized exchange intervention operations are reflected in an expansion of the monetary authority’s balance sheet. As non-monetary liabilities (net repo and LEBAC) increase, external assets increase as well. The yield of international reserves, given by the interest rate they pay and by the evolution of the exchange rate, can offset the financial cost of the liabilities issued to sterilize their acquisition49. In this sense, between early March 2016 and late September this year, the LEBAC and repo stock went from 7.2 percent of GDP to 12 percent of GDP. However, purchases of international reserves in the same period amounted to 4.8 percent of GDP, so the stock of non-monetary liabilities, after discounting acquired foreign currency, remained unchanged (see Figure 5.1).

5.4 BCRA Transfers to the National Treasury in 2018 The transfers the BCRA will make to the National Treasury in 2018, which are included in the Budget bill submitted by the Executive to Congress in September, will total $140 billion. This amount represents a decrease relative to the figure transferred during 2017, both in nominal terms ($10 billion less) and as a share of GDP (it will fall from 1.5 percent of GDP this year to 1.1 percent of GDP in 2018), which shows the monetary authority’s commitment to the goal of lowering inflation (see Figure 5.12). Moreover, the path for the reduction of the fiscal deficit in the medium term foreseen by the Ministry of Finance reinforces the decreasing trend of the BCRA’s transfers in the next few years, and contributes to the goal of reducing inflation.

49 See Exhibit 6 in the January, 2017, IPOM: “Monetary Policy and BCRA balance sheet”.

Table 5.1 | LEBAC stock variation net of acquired reserves since March 2016

million $ % of GDP

LEBAC and Net repos up to Mar‐01‐16 453,077 7.2%

LEBAC and Net repos up to Sep‐30‐17 (1) 1,153,573 12.0%

Reserves purchases by the Central Bank since Mar‐01‐16 (2) 462,129 4.8%

LEBAC and Repos up to Sep‐30‐17, net of acquired reserves (1‐2) 691,444 7.2%

Difference 30‐Sep‐17 vs. 01‐mar‐16 0.0%


54

This level of projected transfers to the Treasury in 2018 does not represent a threat for the evolution of the BCRA’s deficit and the quasi-fiscal balance. Money demand estimations, considering the macroeconomic scenario of the National Budget, suggest that the amount defined is consistent with the 2018 inflation targets. Moreover, the monetary expansion associated with transfers to the public sector will be lower than the expected increase in money demand (approximately $20 billion lower), so it should be possible to reduce the BCRA’s non-monetary liabilities (net swaps and LEBAC) as a share of the monetary base, in the absence of other money issuance sources.

Figure 5.12 | Central Bank transfers to the National Treasury

1.4%

0.5%

4.6%

0.5%

0.8%1.2%

3.3%3.1%

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2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

million $ % of GDPLoans and profit transfers

Use of international reserves

Total in % of GDP (right axis)


Budget Bill


55

Exhibit 5 / Israel’s Inflation Targeting Experience In the early 1990s, a small number of countries began adopting the Inflation Targeting (IT) regime as a monetary policy strategy. Some of the first to do so were New Zealand (1990), Canada (1991), the United Kingdom (1992), Israel (1992), Finland (1993), Australia (1993) and Sweden (1993). The following are the most prominent features of the IT regime:

The announcement of an explicit inflation target (or a series of targets over time). The Central Bank’s commitment to achieving that target, which becomes the primary objective of

the monetary authority, in turn accountable for the achievement of the set goal. The adoption of the interest rate as the primary tool of monetary policy, which clearly signals the

policy’s bias and the monetary authority’s stance towards inflation. Additionally, the monetary policy must be carried out through a prospective evaluation of the inflation dynamics, particularly taking into account inflation forecasts and expectations.

A strategy of institutional transparency, including monitoring and communicating to the public the monetary authority’s vision.

The theoretical consensus on IT regimes highlights a few preconditions that facilitate the regime’s success.50 These preconditions include the operational independence of the monetary authority, the absence of fiscal dominance, the existence of stable and deep domestic financial markets, and a monetary authority not committed to goals related to other nominal variables (particularly, the nominal exchange rate), among others.

50 Eichengreen, Masson, Savastano and Sharma (1999). “Transition Strategies and Nominal Anchors on the road to Greater Exchange Rate Flexibility”. Essays in international finance, Princeton University. Agénor, Pierre-Richard (2002), “Monetary Policy Under Flexible Exchange Rates: An Introduction to Inflation Targeting,” in Loayza, N. and R. Soto: “Inflation Targeting: Design, Performance and Challenges”, Central Bank of Chile, Santiago, Chile.

Figure 1 | Israel. Inflation and Target

‐5

0

5

10

15

20

25

Jan‐90 Nov‐92 Sep‐95 Jul‐98 May‐01 Mar‐04 Jan‐07 Nov‐09 Sep‐12 Jul‐15

y.o.y. % chg.

Inflation

Inflation target

Inflation expectations (12 months)

Source: Central Bureau of Statistics


56

Among the first cases of adoption of IT, the experience of Israel stands out, because, unlike the remaining countries mentioned, and against the theoretical consensus, Israel embarked on the IT path with a relatively high and persistent initial inflation, caused by a high degree of indexation in the economy, a fiscal deficit of about 5 percentage points of GDP, and a relatively narrow scheme of exchange rate bands, with a decreasing trend of depreciation. In fact, the inflation target was first computed as a byproduct of the slow-moving exchange rate bands. This was due to the fact that the rate used to adjust the band’s bounds (the minimum currency depreciation rate) was determined based on the difference between the inflation target and the inflation rate in the rest of the world, so as to prevent a constant real appreciation. As shown in Figure I, while disinflation in Israel was a relatively slow process (it took almost a decade to bring inflation down from levels of approximately 20 percent in the early 1990s to one-digit readings in 1997), it is noteworthy that the adoption of the targeting regime managed to reduce inflation from 20 percent to 10 percent in a single year. Moreover, in the first three years since the regime was put in place, inflation presented deviations relative to the target, both above and below it, and the mean deviation was 1.03 percentage points. In parallel, on the fiscal front, there was a gradual reduction of the government deficit, which went from an average rate of 4.2 percent during the 1990s to one of 2.2 percentage in the 2010s, indicating that a disinflation program can be consistent with fiscal gradualism. In consonance, the weight of government debt in the economy fell from 120 percent of GDP in 1992 to little over 60 percent today.

Among the benefits of the adoption of the IT regime in Israel, besides the significant reduction in the rate of price increases and its variability, we can mention the anchoring of inflation expectations, the broadening of the economy’s planning horizon, and the reduction of the impact of exchange rate movements on domestic prices.51

51 Leiderman, L. (2000). Monetary Policy Rules and Transmission Mechanisms Under Inflation Targeting in Israel. Research Department, Bank of Israel.

Figure 2 | Israel. Fiscal balance and public debt

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% of GDP% of GDPFiscal balance Real GDP Public debt (right axis)

Average90‐99

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Average 10‐16

Source: Central Bureau of Statistics


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Exhibit 6 / Tracing the mortgage market through Internet searches The use of Internet as a source of information can be useful both for researchers and for public officials who monitor market trends. There is a high degree of complementariness between traditional statistics and new data sources, although one advantage of the later is that they are available virtually in real time.52 In the last few months, mortgage credit and the public’s interest in it have grown in line with each other (see Figure 1), in the context of a more dynamic real estate market. This exhibit53 aims at applying Google Trends54 to studying the demand for apartments and mortgage credits, in an attempt to answer the question: Can we anticipate any aggregate movement in this market?

First, we briefly describe the source of the data. Then, following the spirit of standard exercises in the forecast literature, we study the series’ temporal anticipation55 and whether including the measure based on Google searches reduces forecast errors or not. Last, we present some evidence on Acquisition Value Unit (UVA)-denominated loans.

52 It should be pointed that out that working with these new data sets, which are usually large in volume, does not avoid facing the same issues seen in smaller samples: it does not remove per se the potential endogeneity and election bias problems. 53 For more details, see https://ideasdepeso.com/2017/06/26/busquedas-en-internet-googleando-datos/ and https://ideasdepeso.com/2017/09/15/en-busqueda-de-un-credito-hipotecario/. 54 For more details, see https://trends.google.com.ar/trends/ or Choi, H. and H. Varian (2011). “Predicting the Present with Google Trends”. Google Technical Report. 55 Through a Granger Causality Test. Specifically, the test assesses whether a time series (with its leads and lags) anticipates other in time.

Figure 1 | Mortgage loans (y.o.y. % chg.)

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Mortgage loans ‐ Total, in local and foreign currency, of the non‐financial privatesector, balances in thousands of pesos (real deflated by national CPI)

Source: BCRA


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Defining the search Google Trends makes it possible to monitor social interest in various issues for a defined space and time, through a weekly or monthly time series of the relative search intensity for a specific term.56 One of its main advantages is the ability to condition the search for pre-established categories (one of which is the real estate market) in order to obtain more accurate results. Thus, the first step in the analysis is to map the evolution of the search intensity for apartments for sale, compared to apartments for rent. We present those results in Figure 2.

It should be mentioned that the search intensity for the term “apartments for rent” is consistently above that of “apartments for sale”. However, in the last few weeks, the gap between both series has narrowed, and, since mid-March, the latter has been above the former. As a second data set, we want see how a measure constructed based on Google results can anticipate the decision to finance the purchase of a home through a mortgage credit. Therefore, we work with the value obtained from search for the term “mortgage”. Variable of interest Now, we must choose a variable of interest to study the explanatory power of search trends. We consider the data on total new financing through mortgage credits (without distinction between fixed/variable rate, and taking into account both domestic and foreign currency segments) granted to individuals, published by the BCRA. Figure 3 shows both series, in which we filter out the noise of working with high-frequency data by using moving averages (8 periods).

56 First, we normalize the number of searches for a key word or phrase dividing it by total Google searches (controlling for region, date, and category). Then, we re-scale so that the ratio becomes equal to 100 for the maximum popularity within the sample under analysis.

Figure 2 | Google querry Index

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Source: Google Trends (www.google.com/trends)

"apartments for sale (real estate market category)"

"apartments for rent (real estate market category)"


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In more general terms, it is also worth considering the link between searches (potential demand) and acts (deeds). Alternatively, we propose a second exercise taking into account the acts recorded by the Professional Association of Notaries of the City of Buenos Aires (deeds) and the search for apartments for sale.

Figure 3 | Google Querry Index (“Mortgages”) vs New mortgage loans. Last 5years, weekly data

Figure 4 | Google Querry Index ("apartments for sale") vs number of salesoperations. Seasonally adjusted.

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"Mortgage" standardized Google Trends indicator

Standardized mortgage loans

8 per. med. móv. ("Mortgage" standardized Google Trends indicator)

8 per. med. móv. (Standardized mortgage loans)

Source: Google Trends (www.google.com/trends) and BCRA

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"Apartments for sale" (real estate market category)

Sales operations

Source: Google Trends (www.google.com/trends) and Autonomous City of Buenos Aires Notaries Association


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Empirical results Based on a temporal anticipation test57, we should be able to state that the Google trends variable manages to temporally anticipate the number of new mortgage credits by approximately 5/6 weeks. If we analyze the search of apartments for sale and the number of deeds, the results show that the search measure also anticipates the number of deeds by 2 or 3 months. Following several works in the forecast literature, we broaden an autoregressive model (that is, one which only looks at past values of the variable of interest) for mortgage credits, on the one hand, and number of deeds, on the other, with the measure prepared based on Google searches (mortgages and apartments for sale).

(1) yt = α0+ α1 yt‐1+ εt

(2) yt = α0+ α1 yt‐1+ α2 Google Trendst–i + εt For the first case, the addition of the Google Trends measure reduces the forecast error (measure by the root-mean-square error (RMSE) by 1 percent. Moreover, when we study the effect on the number of deeds, the forecast capability improves by 10 percent.58 UVAs A phenomenon worth studying is that of loans denominated in Acquisition Value Units (UVA). In the last few months, approximately 90 percent of new mortgage credits are UVA-denominated. This fact can also be seen in the relative interest on that term in Google Trends, as shown in Figure 5.

57 For brevity’s sake, we do not include the results of the causality test. They are available upon request. 58 The forecast is assessed one step out of the sample for the 2015m1-2017m7 sample based on rolling windows for the different models, in which i stems from the results of temporal anticipation. Once again, results are available upon request.

Figure 5 | Google Querry Index (UVA Credit) and UVA Mortgage Loans

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Querry Index (UVA Credit)

UVA Stock Mortgage Loans

Source: Google Trends (www.google.com/trends) and BCRA


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In principle, both series move in a synchronized fashion (in fact, their correlation coefficient is above 0.9). Seeing as both series are relatively short, studying one’s temporal anticipation over the other does not yield significant results. However, as more data becomes available, a more detailed analysis will be possible. Conclusions Internet, particularly in searches by individuals in the main search engines, opens up a wide range of options to supplement the analysis and follow-up of various actors in different markets. Even from a regulatory or normative point of view, it enables us to anticipate certain developments and improve the models currently used in central banks and the public sector. References Askitas, N. (2015). “Trend-Spotting in the Housing Market – a significant correlation with the US national S&P/Case Shiller Home Price Index”. Askitas, N. and Zimmermann, K. (2011). “Detecting Mortgage Delinquencies”. IZA Discussion Paper No. 58. Ayub, P and Raffin, M. (2017). “Créditos Hipotecarios UVA: ¿Es un instrumento que puede ampliar el acceso a la vivienda?”. In Ideas de Peso del BCRA. Bholat, D. (2015). “Big data and central banks”. BOE Quarterly Bulletin 2015 Q1. Bank of England. Blanco, Emilio (2014). “Herramientas de Big Data: ¿podemos aprovechar Google Trends para pronosticar variables macro relevantes?”. MIMEO, available here. Coble, D. and Pincheira, P. (2017). “Now-Casting Building Permits with Google Trends”. DOI: 10.13140/RG.2.2.36321.10082. Choi, H. and Varian, H. (2011). “Predicting the Present with Google Trends”. Google Technical Report. Choi, H. and Varian, H. (2009). “Predicting initial claims for unemployment insurance using Google Trends”. Google Technical Report. Dabusti, F. (2017). “Préstamos con UVA: el alargamiento de plazos se hace más importante”. In Ideas de Peso del BCRA. van Veldhuizen, S., Vogt, B. and Voogt, B. (2016). “Internet searches and transactions on the Dutch housing market”. CPB Netherlands Bureau for Economic Policy Analysis Discussion Paper No.325.


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Abbreviations and Acronyms €: Euro AFCP: Asociación de Fabricantes de Cemento Portland AFIP: Administración Federal de Ingresos Públicos. Federal Administration of Public Revenues APR: Annual percentage rate AUH: Asignación Universal por Hijo. Universal Child Allowance Avg.: Average BADLAR: Buenos Aires Deposits of Large Amount Rate (Interest rates for deposits over 1 million pesos for terms of 30-to-35 days) BCBA: Bolsa de Comercio de Buenos Aires. Buenos Aires Exchange BCRA: Banco Central de la República Argentina. Central Bank of Argentina b.p.: basis points CABA: Ciudad Autónoma de Buenos Aires. Autonomous City of Buenos Aires Bontes: Bonos del Tesoro. National Treasury bonds CEMBI+: Corporate Emerging Market Bond Index Plus CEMBI+AR: Corporate Emerging Market Bond Index Plus Argentina CER: Coeficiente de Estabilización de Referencia. Reference Stabilization Coefficient Chg.: Change CNV: Comisión Nacional de Valores. National Securities Commision CSJN: Corte Suprema de Justicia de la Nación. National Supreme Court of Justice DJVE: Declaraciones Juradas de Ventas al Exterior. Export Sales Affidavit ECB: Banco Central Europeo. European Central Bank ECLAC: Economic Commission for Latin America and the Caribbean EDP: Equipo Durable de Producción. Production durable equipment EMAE: Estimador Mensual de la Actividad Económica. Monthly Economic Activity Indicator EMBI+: Emerging Markets Bond Index Plus EMBI+AR: Emerging Markets Bond Index Plus Argentina EMBIG: Emerging Market Bond Index Global EPH: Encuesta Permanente de Hogares. Permanent household survey

f: Forecast Fed: United States Federal Reserve FIEL: Fundación de Investigaciones Económicas Latinoamericanas FOB: Free on Board FOMC: Comité Federal de Mercado Abierto. Federal Open Market Committee GBA: Gran Buenos Aires. Greater Buenos Aires GDP: Gross domestic product IAMC: Instituto Argentino de Mercado de Capitales IBIF: Inversión Bruta Interna Fija. Gross domestic fixed investment ICC: Índice de Confianza del Consumidor elaborado por la Universidad Torcuato Di Tella. Consumer Confidence Index computed by the Torcuato Di Tella University ICC-INDEC: Índice del Costo de la Construcción. Construction Cost Index IGA-OJF: Índice General de Actividad de Orlando J. Ferreres. General Activity Index released by Orlando J. Ferreres ILA: Índice Líder de la Actividad. Leading Activity Index IMF: International Monetary Fund INDEC: Instituto Nacional de Estadística y Censos. National Institute of Statistics and Censuses INML: Índice de Novillos del Mercado de Liniers IPC CABA: Índice de Precios al Consumidor de la Ciudad de Buenos Aires. Consumer price index for the City of Buenos Aires IPC GBA: Índice de Precios al Consumidor del Gran Buenos Aires. Greater Buenos Aires Consumer price index IPC-NP: Indicador Nacional Ponderado. Weighted national consumer price index IPC San Luis: Índice de Precios al Consumidor de la Provincia de San Luis. Consumer price index for the Province of San Luis IPIB: Índice de Precios Internos Básicos. Basic industrial price index IPIM: Índice de Precios Internos al Por Mayor. Domestic wholesale price index IPMP: Índice de Precios de las Materias Primas. Commodity price index IPOM: Informe de Política Monetaria. Monetary Policy Report


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ITCRM: Índice de Tipo de Cambio Real Multilateral. Real Multilateral Exchange Rate Index LAC: Latin American Consensus Forecasts LEBAC: Letras del Banco Central. BCRA bills LFPIF: Línea de financiamiento para la producción y la inclusión financiera M2: Billetes y monedas + cuasimonedas en circulación + cuentas corrientes en $ y cajas de ahorro en $. Notes and coins + quasimonies + $ savings and current accounts m.a.: moving average MATBA: Mercado a Término de Buenos Aires MERVAL: Mercado de Valores de Buenos Aires MIP: Matriz insumo-producto. Input-output matrix MOA: Manufacturas de Origen Agropecuario. Manufactures of agricultural origin MOI: Manufacturas de Origen Industrial. Manufactures of industrial origin MSCI: Morgan Stanley Capital International Index MTEySS: Ministerio de Trabajo, Empleo y Seguridad Social. Ministry of Labor, Employment and Social Security MULC: Mercado Único y Libre de Cambios. Single free exchange market National IPC: Índice de Precios al Consumidor Nacional. National consumer price index NOBAC: Notas del Banco Central. BCRA notes OPEC: Organization of the Petroleum Exporting Countries p.p.: Percentage points PCP-BCRA: Predicción contemporánea del BCRA

PMI: Purchasing Managers’ Index PP: Productos primaries. Primary products R$: Brazilian Real REM: Relevamiento de Expectativas de Mercado. Market Expectations Survey REPO: Repurchase Agreement ROE: Registros de Operaciones de Exportación. Export operations records Rueda REPO: Tasa de interés promedio de las operaciones a 1 día hábil entre entidades financieras en el mercado garantizado s.a.: Seasonally adjusted TFP: Productividad total de los factores. Total factor productivity TN: Tesoro Nacional. National Treasury UCI: Utilización de la capacidad instalada. Installed capacity utilization US$: United States Dollar UTA: Unión Tranviarios Automotores UTDT: Universidad Torcuato Di Tella. Torcuato Di Tella University UVA: Unidad de Valor Adquisitivo. Acquisition Value Unit VAR: Modelo de Vectores Autorregresivos. Vector Autorregresive Models VAT: Value added tax VBP: valor bruto de producción. Gross production value y.o.y.: year-on-year YPF SA: Yacimientos Petrolíferos Fiscales Sociedad Anónima

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