Determinants of inflation in Romania
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Transcript of Determinants of inflation in Romania
Determinants of inflation
in Romania
ACADEMY OF ECONOMIC STUDIES BUCHARESTDOCTORAL SCHOOL OF FINANCE AND BANKING
Supervisor:Prof. MOISĂ ALTĂR
Student: FIROIU IULIA
BUCHAREST- July 2007-
Introduction
• Monetary inflation - when the supply of money is greater than the level of output (pure monetary theory – Friedman (1969))
• Wage inflation - wages increases more than labor productivity, raising the unit labor costs
• The transmission of import prices in a foreign currency leads to general domestic inflation.
I assumed there are three sources of inflation:
The objective of the paper is to provide some answers to the question: how has inflation been reduced in Romania and what policies proved to be effective in stabilizing economy.
1. I identified a long-run equation in the monetary and labor sectors;
2. I estimated the inflation equation by incorporating the error correction terms derived from each co integration relationship into the short run model (ECM Model).
Money market
M2(Y, Dr, RER)
Goods market
ΔP (ULCt-Pt, RER)
VAR model
Inflation (ΔP)
Real money (M2R)
Real Exchange Rate (RER)
Labor shares (St=ULCt-Pt)
deviations from the long-run equilibrium
Monthly data:
The Balassa-Samuelson Effect:
The productivity grows faster in
the tradable sector
The wage increases in both sectors
The prices of non-tradable goods rise
The overall price level in the economy increases
I analyzed the impact of the difference in productivity between tradable and non-tradable sectors on inflation.
Most of Central Europe’s transition economies have experienced a very rapid productivity growth, especially in the industrial sector.
Quarterly data:
Melisso Boschi and Alessandro Girardi (2005) - determinants of inflation in the Euro Area economy – find a stable long-run relation connecting the price index, labor shares and import prices.
MONEY DEMAND:
LITERATURE REVIEW
Brada and Kutan (1999) - three transition countries (Czech Republic, Hungary and Poland),
-inflation is determined largely by past inflation and by foreign prices;- monetary policy is relatively ineffective
Markup Model:
De Grauwe and Skudelny (2000) test the Balassa-Samuelson effect for 13 of the 15 EU member countries ( period 1971-1995);
- differences in productivity growth between sectors translates into a change in CPI with a coefficient of 0.3.
Balassa-Samuelson Effect:
Monthly data:realmon_sa = Log (RON M2 / CPI) seasonally adjusted (with Tramo/Seats)ppi_sa = Industrial production index (December 1999=100) seasonally adjusted (with Tramo/Seats) (%)lysa = Log (ppi_sa); seasonally adjusted (with Tramo/Seats)depr = Nominal deposit rate applied by banks to non-governamental non-bank customers (%)e= Nominal exchange rate RON/EURexch= Log (e)p = Log (HICP Romania_dec97);pf = Log (HICP Eur13_dec97)exchrate ( pf + exch-p) =Real exchage rate RON/ EUR based on HICP.
1. LONG RUN EQUILIBRIUM ON THE MONEY MARKET
Md = f(Y ; r; x)
Md = money demand in real terms; Y = the level of economic activity, r = the opportunity cost of holding money, and x is a vector
of other variables which will be included in the model.
Johansen Cointegration Test for the money demand function:
No deterministic trend (restricted constant) – 4 lags in the VAR
Eigenvalue Trace Statistic
5%
Critical Value
1%
Critical Value
None ** 0.460440 107.1216 53.12 60.16
At most 1 ** 0.337411 58.37854 34.91 41.07
At most 2 ** 0.175036 25.86216 19.96 24.60
At most 3 * 0.126243 10.66132 9.24 12.97
*(**) denotes rejection of the hypothesis at the 5%(1%) level
Trace test indicates 3 cointegrating equation(s) at the 1% level
realmon_sa = 7.290638+0.651103 * lysa-0.049206 * depr -1.478535 * exchrate
The residual:
Emm = realmon_sa-7.29 -0.65 * lysa +0.049*depr+ 1.47 * exchrate ~I(0)
realmon_sa~I(1)
lysa ~ I(1);
depr ~ I(1);
exchrate~I(1).
I tested in VEC - the restriction B(1,1)=1 and B(1,2)=-1 (3 lags in VAR).
realmon_sa = 5.620331+lysa-0.034615*depr-1.297562*exchrate
The residual:Emmres = realmon_sa - 5.620331- lysa +0.034615*depr+1.297562*exchrate ~ I(0)
-.4
-.2
.0
.2
.4 10.8
11.2
11.6
12.0
12.4
12.8
2000 2001 2002 2003 2004 2005 2006
Residual Actual Fitted
Actual vs fitted M2
The monetary policy has been rather passive and subordinate to other policy objectives (the exchange rate policy).
Variable Coef. Std. Error t-Statistic Prob.
c 0.036557 0.003279 11.14961 0.0000
DEPR -0.001249 0.001134 -1.101944 0.2739
DLYSA -0.840221 0.239528 -3.507811 0.0008
DEXCHRATE -0.016490 0.041299 -0.399267 0.6908
EMM(-1) -0.007218 0.004355 -1.657527 0.1014
R-squared 0.510414 Mean dependent var
0.014026
Adjusted R-squared
0.485307 S.D. dependent var
0.013691
S.E. of regression
0.009822 Akaike info criterion
-6.350024
Sum squared resid
0.007525 Schwarz criterion
-6.204310
Log likelihood 268.5260 F-statistic 20.32960
Durbin-Watson stat
1.525251 Prob(F-statistic)
0.000000
Error Correction Equation for the real M2 from the unrestricted VAR:
Variable Coefficient Std. Error t-Statistic Prob.
C 0.034874 0.002525 13.80948 0.0000
DEPR -0.001425 0.001115 -1.278146 0.2050
DLYSA -0.703238 0.246116 -2.857338 0.0055
DEXCHRATE
-0.015608 0.040711 -0.383393 0.7025
EMMRES(-1)
-0.010571 0.004709 -2.244880 0.0276
R-squared 0.523928 Mean depend.Var
0.014026
Adjusted R-squared
0.499514 S.D. dependent
var
0.013691
S.E. of regression
0.009686 Akaike info criterion
-6.378014
Sum squared resid
0.007317 Schwarz criterion
-6.232301
Log likelihood
269.6876 F-statistic 21.46020
Error Correction Equation for the real M2 from the restricted VAR
If there is an excess of money in the present month, in the next monththe agents will reduce their money holdings.
Stability Tests for the money demand Error-Correction Equation
-30
-20
-10
0
10
20
30
2001 2002 2003 2004 2005 2006
CUSUM 5% Significance
Both specifications are stable in terms of the parameters.
-.02
-.01
.00
.01
.02
.03
.04
.05
.06
2001 2002 2003 2004 2005 2006
Recursive C(1) Estimates ± 2 S.E.
-2.0
-1.6
-1.2
-0.8
-0.4
0.0
0.4
2001 2002 2003 2004 2005 2006
Recursive C(2) Estimates ± 2 S.E.
-.15
-.10
-.05
.00
.05
.10
.15
.20
2001 2002 2003 2004 2005 2006
Recursive C(3) Estimates ± 2 S.E.
-.004
-.003
-.002
-.001
.000
.001
.002
.003
2001 2002 2003 2004 2005 2006
Recursive C(4) Estimates ± 2 S.E.
-.03
-.02
-.01
.00
.01
2001 2002 2003 2004 2005 2006
Recursive C(5) Estimates ± 2 S.E.
Pairwise Granger Causality Tests Null Hypothesis: 1 lag
Prob2
lagsProb
3 lagsProb
4 lagsProb
5 lagsProb
6 lagsProb
12 lags Prob
LYSA does not Granger Cause REALMON_SA
1.9E-09
5.9E-05
0.00163
0.00578
0.06937
0.17505
0.31068
EXCHRATE does not Granger Cause REALMON_SA
0.12267
0.37732
0.68928
0.73686
0.76687
0.75280
0.98586
DEPR does not Granger Cause REALMON_SA
0.00083
0.09904
0.02266
0.05907
0.02882
0.08473
0.00935
RESULTS:
• Between the real money M2 (realmoney_sa) and the industrial production (lysa) there is a short term causality relationship.
• The real exchange rate (exchrate) doesn’t seem to influence the real money M2.
• There is also a long term relationship between M2 and the deposit rate.
2. The markup model
zt=pt – γ * ulct – δ * pmt – η * πt = qt – η * πt (1) zt= γ*(pt-ulct)+ δ*(pt-pmt)- η*πt (2) β1*(ulct-pt)+β2*( pmt-pt) + et = πt (3)
where zt = retail markup over costs at time t,
qt is the “gross markup” , πt= Δpt = inflation rate;
γ>=0 and δ>=0 = elasticities of the price level with respect to unit labor costs and import costs;
(satisfy the homogeneity restriction γ+ δ=1);
η = inflation cost; β1= -γ/η, β2= -δ /η, and et= -zt/η
Iprod = Labour productivity index in industry (December 1999 =100); ratio between index of industrial production and index of number of employees; prod = Log (Iprod);st=ulct-p =Labor share = wage-prod-p = realwage - prod
Monthly data:CPI = Consumer Price Index (December 1999=100); p = Log (CPI); inflation = p-p(-1)
Johansen Co integration Test for the markup model
No deterministic trend (restricted constant) – 5 lags in the VAR
Eigenvalue Trace statistic
5% Critical Value
1 % Critical Value
None ** 0.352548 69.86704 34.91 41.07
At most 1 **
0.330768 36.39436 19.96 24.60
At most 2
0.068566 5.469308 9.24 12.97
*(**) denotes rejection of the hypothesis at the 5%(1%) level
Trace test indicates 2 cointegrating equation(s) at both 5% and 1% levels
inflation=0.036927*st+0.002914*exchrate+0.211697
inflation~ I(1);st ~ I(1);exchrate~I(1).
The equilibrium error term: elab=inflatie-0.036927*st-0.002914*exchrate-0.211697
0
4
8
12
16
20
-0.02 -0.01 0.00 0.01
Series: ELABSample 2000:02 2006:12Observations 83
Mean -0.003539Median -0.003722Maximum 0.011756Minimum -0.024388Std. Dev. 0.006734Skewness -0.506726Kurtosis 3.857334
Jarque-Bera 6.093952Probability 0.047502
-.03
-.02
-.01
.00
.01
.02
2000 2001 2002 2003 2004 2005 2006
ELAB
Normality and stationarity tests for the residual from the markup model
Error Correction Equation for inflation:
Variable Coef. Std. Error t-Statistic Prob.
C 0.002140 0.002776 0.770865 0.4433
DINFLATIE(-1) -0.161178 0.151545 -1.063562 0.2911
DINFLATIE(-2) -0.115941 0.110307 -1.051076 0.2967
DEXCHRATE -0.042374 0.026654 -1.589775 0.1163
DST -0.001795 0.014535 -0.123514 0.9020
DREALMONSA -0.020505 0.062102 -0.330173 0.7422
ELAB(-1) -0.802889 0.190802 -4.207977 0.0001
EMMRES(-1) -0.005609 0.002447 -2.291927 0.0248
R-squared 0.559645 Mean depen. var
-0.000492
Adjusted R-squared
0.516833 S.D. dependent var
0.007882
S.E. of regression 0.005479 Akaike info criterion
-7.481181
Sum squared resid 0.002161 Schwarz criterion
-7.242978
Log likelihood 307.2472 F-statistic 13.07206
Durbin-Watson 1.617832 Prob(F-stat) 0.000000
• If wages affect prices, their effect is realized mainly through the magnitude of disequilibrium in the labor sector rather than its unit impact on prices. The speed of adjustment towards the equilibrium is very high (80.28% is absorbed in the next period). This suggests that when the economy is shocked away from the long-run relationship, adjustment back to equilibrium is realized by changes in the rate of inflation through actions of the monetary authorities.
• The coefficient of the error correction term from the money demand relationship is small indicating that there is little effect of excess money on inflation. This is in line with a finding by Brada and Kutan (1999), who suggested that monetary policy in Poland has been used mainly to support the exchange rate policy.
-.015
-.010
-.005
.000
.005
.010
.015
2001 2002 2003 2004 2005 2006
Recursive Residuals ± 2 S.E.
Recursive Residuals Tests for the Error-Correction equation for inflation
This figure shows that there is little evidence of regime shifts: variations in the inflation variable are within +/-5% innovation errors.
Impulse Response (GIR) functions
-.004
-.002
.000
.002
.004
.006
.008
1 2 3 4 5 6 7 8 9 10
Response of INFLATION to INFLATION
-.004
-.002
.000
.002
.004
.006
.008
1 2 3 4 5 6 7 8 9 10
Response of INFLATION to REALMON
-.004
-.002
.000
.002
.004
.006
.008
1 2 3 4 5 6 7 8 9 10
Response of INFLATION to EXCHRATE
-.004
-.002
.000
.002
.004
.006
.008
1 2 3 4 5 6 7 8 9 10
Response of INFLATION to ST
-.02
-.01
.00
.01
.02
.03
.04
1 2 3 4 5 6 7 8 9 10
Response of REALMON to INFLATION
-.02
-.01
.00
.01
.02
.03
.04
1 2 3 4 5 6 7 8 9 10
Response of REALMON to REALMON
-.02
-.01
.00
.01
.02
.03
.04
1 2 3 4 5 6 7 8 9 10
Response of REALMON to EXCHRATE
-.02
-.01
.00
.01
.02
.03
.04
1 2 3 4 5 6 7 8 9 10
Response of REALMON to ST
-.03
-.02
-.01
.00
.01
.02
.03
1 2 3 4 5 6 7 8 9 10
Response of EXCHRATE to INFLATION
-.03
-.02
-.01
.00
.01
.02
.03
1 2 3 4 5 6 7 8 9 10
Response of EXCHRATE to REALMON
-.03
-.02
-.01
.00
.01
.02
.03
1 2 3 4 5 6 7 8 9 10
Response of EXCHRATE to EXCHRATE
-.03
-.02
-.01
.00
.01
.02
.03
1 2 3 4 5 6 7 8 9 10
Response of EXCHRATE to ST
-.03
-.02
-.01
.00
.01
.02
.03
.04
1 2 3 4 5 6 7 8 9 10
Response of ST to INFLATION
-.03
-.02
-.01
.00
.01
.02
.03
.04
1 2 3 4 5 6 7 8 9 10
Response of ST to REALMON
-.03
-.02
-.01
.00
.01
.02
.03
.04
1 2 3 4 5 6 7 8 9 10
Response of ST to EXCHRATE
-.03
-.02
-.01
.00
.01
.02
.03
.04
1 2 3 4 5 6 7 8 9 10
Response of ST to ST
Response to Generalized One S.D. Innovations ± 2 S.E.
• A shock in the inflation equation implies only a temporary effect on the next evolution of inflation.
• It takes only two months for the shock to real money to exert a maximum influence on prices, that is 1%
• The response of prices to real wage shocks shows a cyclical pattern over the first six months, after that the shock is absorbed.
• The impact response of prices, given a shock to exchange rate, is 1% in the second month and after three months the shock dies out.
Period S.E. INFLATION REALMON EXCHRATE ST
1 0.005285 100.0000 0.000000 0.000000 0.000000
2 0.005645 87.86440 7.145527 4.819774 0.170294
3 0.005658 87.46893 7.116406 4.920808 0.493855
4 0.005701 86.84927 7.093243 4.905791 1.151699
5 0.005770 85.28335 7.902958 4.793715 2.019977
6 0.005820 83.84248 9.066248 5.059694 2.031573
7 0.005831 83.63422 9.035602 5.144102 2.186080
8 0.005849 83.12401 9.277654 5.113768 2.484568
9 0.005864 82.82599 9.409582 5.127039 2.637392
10 0.005870 82.72798 9.393263 5.127278 2.751483
Variance Decomposition of Inflation
Real money seems to be the main factor of influence for inflation; the second place is taken by the real exchange rate. The labor share (ulct-pt) has little consequences on variations of inflation.
3. The Balassa – Samuelson Model
It is assumed that economies are characterized by two different production functions with constant returns to scale, one for the production of tradable (mainly industrial goods), and one for non-tradable (mainly services).
b (1-b)1. Yt = At * (Lt) + (Kt) c (1-c) 2. Ynt = Ant * (Lnt) + (Kt) ,
where Y = output, A = total factor productivity, L = labour, K = capital, t / nt =tradable / non-tradable good sectors, b and c = labor intensity in the two sectors.
First, I will test the relation between unit labor costs and prices in industry:
ln Ptrad = ln b + β * ln ULCt + εt, where β is expected to be positive and equal to 1.
Quarterly data:CPI = Consumer Price Index (2000:Q1=100) ; p = Log(CPI); inflation = p-p(-1) ;CPItrad =Consumer Price Index in the tradable sector (2000:Q1=100); ptrad = Log(CPItrad);I_prod_trad = Labour productivity index in the tradable sector (2000:Q1=100) = ratio GDP and the number of employees in the tradable sector; prodtrad = Log(I_prod_trad);I_prod_nontrad = Labour productivity index in the tradable sector (2000:Q1=100); ratio between GDP and the number of employees in the nontradable sector; prodnontrad = Log(I_prod_nontrad);difprod = prodtrad-prodnontrad;Iulct = Unit labor cost index in the tradable sector (ratio between index of real nominl net wage in industry and index of industrial production); ulct = Log (Iulct)
Secondly, I will test the Balassa - Samuelson hypothesis: the total price level should be driven by the productivity differential between the tradable and non tradable goods sectors
VAR Lag Order Selection Criteria
Endogenous variables ptrad ulct
Lag LogL LR FPE AIC SC HQ
0 33.9431
2
NA 0.000294
-2.457163
-2.360386
-2.429295
1 83.7243
3
88.074
45*
8.70E-06*
-5.978795*
-5.688465*
-5.895190
*
2 85.9889
1
3.6581
74
1.00E
-05
-5.845301
-5.361418
-5.705960
* indicates lag order selected by the criterion-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
Inverse Roots of AR Characteristic Polynomial
inflation ~I(1);ptrad ~ I(1);ulct ~ I(1);difprod ~ I(1).
Stability VAR (1)
Johansen Cointegration Test - the relationship between prices and unit labour costs in the tradable
sector
No deterministic trend (restricted constant) – 1 Lag
Eigenvalue TraceStatistic
5 %Critical Value
1 %Critical Value
None ** 0.528436 34.72969 19.96 24.60
At most 1 **
0.442369 15.18550 9.24 12.97
*(**) denotes rejection of the hypothesis at the 5%(1%) level
Trace test indicates 2 cointegrating equation(s) at both 5% and 1% levels
ptrad=1.026758*ulct+6.017215
=> the difference between net nominal wages and productivity in industry translates fully into the tradable prices.
Endogenous variables: INFLATIE DIFPROD
Lag LogL LR FPE AIC SC HQ
0 74.83339 NA 3.33E-06
-6.93651 -6.83703 -6.91492
1 87.67558 22.015 1.44E-06
-7.77862 -7.48019 -7.71385
2 97.61135 15.140 8.31E-07
-8.34393 -7.84654 -8.23599
3 104.6049 9.3247 6.46E-07
-8.62903 -7.93268 -8.47791
4 115.3903 12.326* 3.62E-07*
-9.27527 -8.379* -9.08096
5 120.3628 4.7356 3.69E-07
-9.367* -8.27362 -9.130*
* indicates lag order selected by the criterion
VAR Lag Order Selection Criteria
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
Inverse Roots of AR Characteristic Polynomial
Stability VAR (4)
Johansen Cointegration Test - the relationship between the productivity differential and inflation
Trend assumption: No deterministic trend (restricted constant) – 4 lags in the VAR
Hypothesized
No. of CE(s)
Eigenvalue
TraceStatistic
5 %Critical Value
1 %Critical Value
None ** 0.498675 25.20869 19.96 24.60
At most 1 * 0.365774 10.01768 9.24 12.97
*(**) denotes rejection of the hypothesis at the 5%(1%) level
Trace test indicates 2 cointegrating equation(s) at the 5% level
Trace test indicates 1 cointegrating equation(s) at the 1% level
inflation=0.15*difprod-0.002341.
-.04
-.02
.00
.02
.04
.06
.08
.10
2000 2001 2002 2003 2004 2005 2006
RES02
The stationarity test for the residual
Conclusions:
• There is a long-run stable relationship between M2 and the other three variables: the index of industrial production the deposit interest rate and the real exchange rate
• I found that there is little effect of excess money on inflation. In Romania, the same as in other transition economies, the monetary policy was mainly subordinated to the exchange rate policy.
• Co integration techniques and error correction models used to estimate the relationship between markup and inflation dynamics show a relation between prices and marginal costs and that inflation error-corrects towards this equilibrium.
• According to the Johansen test the production costs influence inflation. That’s why, in order to assure the stability of prices, the fiscal authorities should play an important role in the inflation process.
• the Error-correction Model (ECM) for inflation revealed that, on the short-term basis, the policy of wages affects inflation in an indirect way through the magnitude of disequilibrium in the labor sector rather than its unit impact on prices.
• The Co integration Tests of the Balassa - Samuelson hypothesis show that in the industry sector the unit labor costs fully translates into the level of prices and that the productivity growth differential between sectors has a positive effect on inflation.
Conclusions: