Inter-sectoral Production Linkages in Slovenia:

An Input-Output Analysis

Daniela Muhaj – Johns Hopkins UniversityUroš Geršak – Banka Slovenije

September 2015

Views and conclusions expressed in this presentation should not be taken to represent the view of Banka Slovenija.

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Agenda

• Research Project• Data Overview• Results– Multipliers

– Key Sector

– Multiplier Product Matrix

• Key Findings• Future Research

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Research Project

Motivation– “Data gossiping” or “data analysis”?– Network analysis, input-output tables, financial flows

Objective– Understanding the causes and effects of the financial crisis on

Slovenian enterprises from a real and financial perspective

Structure– Three part project:

• Macro-Real • Micro-Enterprise • Real-Financial

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Data Sources

• Symmetric IO tables 2005, 2009 and 2010

• Methodology: ESA 1995 data

• Classifications CPA 2002 / Nace Rev. 1.1 (2005) CPA 2008 / Nace Rev. 2 (2009 & 2010)

• Bridge tables- Aggregated (6 industries)- By section (13 industries) - By division (60 industries / 64 industries)

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1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

-10

-8

-6

-4

-2

0

2

4

6

87

-8

Real GDP growth rates in %

Data Overview

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Data Overview

• Domestic production

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• Total output, intermediate cons., valued added

Data Overview

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Data Overview

-20

-15

-10

-5

0

5

10

15

20

4.75.9 6.8

5.1

1.3

-2.3

1.33.0

-16.3

14.4

Average growth rate per year in %

2005-20092010

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Results: Multipliers

Column1Agriculture Manufacturing Construction Trade

Business services

Other

  Output multiplier

2005 1.5717 1.4799 1.9986 1.5788 1.4290 1.3491

2009 1.6298 1.6465 2.0819 1.6217 1.4093 1.3600

2010 1.5724 1.6130 2.1189 1.6256 1.4149 1.3560

  Imported goods and services m.

2005 0.1915 0.4874 0.3179 0.1901 0.1054 0.1158

2009 0.1989 0.4171 0.2774 0.1815 0.1157 0.1176

2010 0.2126 0.4641 0.3016 0.1991 0.1212 0.1255

  Value added multiplier

2005 0.7864 0.5020 0.6435 0.7835 0.8747 0.8386

2009 0.7709 0.5716 0.6936 0.7919 0.8659 0.8369

2010 0.7630 0.5252 0.6736 0.7750 0.8604 0.8289

• Multiplier Analysis: Output, Imports & Value Added

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Results: Key Sector

Understanding the model– Forward linkages

• Interconnection of a sector with the “upstream” sectors from which it purchases inputs

• Direction of causation in the demand-side model

– Backward linkages• Interconnection of a sector with the “downstream” sectors

to which it sells output• Direction of causation in the supply-side model

Evaluating economic connectedness – Mechanism for identifying “key” or leading sectors

• Possibility of studying the evolution of inter-sectoral connectedness

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Results: Key Sector

• Backward linkages oriented: Construction• Forward linkages oriented: Business Services & Manufacturing

– Trade*• Weakly linkages oriented: Agriculture

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Results: Multiplier Product Matrix

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Results: Multiplier Product Matrix

• Visualization technique capturing structural economic changes

• Descending rank-sized hierarchies − Calculated from backward & forward linkages

• Interpretation of the diagrams− Bar height captures the strength of the inter-sectoral relationship− 2005 layout is superimposed on 2009 & 2010 landscapes

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Results: Multiplier Product Matrix

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Results: Multiplier Product Matrix

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Results: Multiplier Product Matrix

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Results: Key Findings

• Construction sector has strong and consistent inter-sectoral linkages • Most robust backward linkages with manufacturing, business services

and trade• Respectively the top three sectors providing inputs to construction

• Manufacturing has the strongest forward linkages with construction and trade

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Results: Key Findings

• There is no key sector in Slovenia– However, construction has consistently been an important sector

• Construction activities are highly interdependent with activities of other sectors for inputs.

• Observed structural change in the Slovenian economy– Fluctuations of inter-sectoral relationships

• Sectoral production is highly sensitive to changes in other sectors’ output

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Future Research

• Consolidate the industry classification systems– Comparable results at the disaggregated level

• Complete the rest of the macro analysis– Impact analysis– Extraction method

• Incorporate Network Analysis – Visualizing the inter-sectoral linkages over time

• Constant prices data• Disaggregated data

• Expand the analysis at the enterprise micro level– Use balance sheet data for survival analysis

• Connect the real and financial effects of the crisis in Slovenia– Financial flow data and contagion analysis

Inter-sectoral Production Linkages in Slovenia:

An Input-Output Analysis

Daniela Muhaj – Johns Hopkins UniversityUroš Geršak – Banka Slovenije

September 2015

Views and conclusions expressed in this presentation should not be taken to represent the view of Banka Slovenija.