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Fiscal Policy in Hard Times: A Fuzzy-Set QCA of Fiscal Policy Reactions to the Financial Crisis

Finanzpolitik in schweren Zeiten – Eine Fuzzy-Set QCA der konjunkturpolitischen Reaktionen auf die Finanzkrise

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Abstract

During the international financial and economic crisis of 2008–2010 all OECD member states were facing similar albeit varying challenges. However, their reactions to the crisis greatly differed. While many states passed extensive economic stimulus packages, others solely relied on a restrictive fiscal policy even in times of economic crisis. The composition of the fiscal packages also greatly varied. While some states increased public expenditure and expanded state investments, others enacted considerable tax reductions, thus focusing on an economic stimulus by forgoing public revenue.

This paper aims to identify the main political determinants of the different fiscal policy reactions of the OECD member states to the economic crisis. The centerpiece of the comparative analysis consists of political economic determinants of the size and composition of the fiscal packages. A fuzzy-set Qualitative Comparative Analysis serves to identify the driving forces behind the fiscal policy reactions to the crisis. The conditions are derived from partisan political theory and the “Varieties of Capitalism” approach while other factors are controlled for.

Zusammenfassung

Obwohl die OECD-Staaten durch die Finanz- und Wirtschaftskrise 2008–2010 vor vergleichbaren Herausforderungen standen – wenn auch in unterschiedlichem Ausmaß – haben sie in hohem Maße unterschiedlich auf die Krise reagiert: Viele Staaten verabschiedeten umfangreiche Konjunkturpakete, andere wiederum fuhren auch in der Krise eine restriktive Fiskalpolitik. Auch bei der Zusammensetzung der Konjunkturpakete offenbaren sich fundamentale Unterschiede. Während einige Staaten im Rahmen ihrer Konjunkturpakete vor allem die Staatsausgaben erhöhten, reagierten andere mit deutlichen Steuervergünstigungen und setzten somit auf einen Konjunkturimpuls durch den Verzicht auf Mittel auf der Seite der Staatseinnahmen.

Ziel des Aufsatzes ist es, die treibenden politikwissenschaftlichen Erklärungsfaktoren für diese unterschiedlichen fiskalpolitischen Reaktionen der Jahre 2008–2010 auf die Wirtschafts- und Finanzkrise zu identifizieren. Im Fokus des Aufsatzes wird hierbei die Identifikation von polit-ökonomischen Erklärungsfaktoren für den Umfang und die Ausgestaltung der Konjunkturpakete stehen. Als outcome wird sowohl die Varianz des Umfangs als auch die Zusammensetzung der Konjunkturpakete hinsichtlich des Verhältnisses von staatlicher Einnahme- und Ausgabeseite zueinander untersucht.

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Notes

  1. The sample of this study consists of the 30 states that were members of the OECD during the entire period of the financial crisis. The four countries that acceded the OECD in 2010 (Chile, Slovenia, Israel and Estonia) are not included in the sample.

  2. In contrast, Cusack and Beramendi (2006) argue that CMEs and LMEs raise different kinds of taxes. While CMEs tend to have higher levels of income taxation, LMEs tend to increase capital and corporate taxes (Cusack and Beramendi 2006 p. 48).

  3. The values of the conditions were derived from the CPDS-I data set containing data for 23 OECD member countries (Armingeon et al. 2010), the CPDS-III data set (Armingeon et al. 2011) and OECD Statistics (2011). (http://www.oecd.org/document/34/0,3343,en_2649_33927_40917154_1_1_1_1,00.html).

  4. The calibration of the conditions and the assignment of fuzzy-set values to all countries are outlined in Appendix 1 below.

  5. As I expect some conditions to have a negative effect on the size of FSP (i.e. the development of the central governmental debt and the national public debt in 2008), I report the results for the complements of the conditions as well.

  6. The consistency value measures the degree to which the conditions are indeed empirically necessary or sufficient for the outcome. The coverage indicates how much of the outcome can be explained by the conditions, i.e. how relevant the conditions or the conjunctions of conditions are for the outcome (Blatter et al. 2007, p. 225). Blatter et al. (2007) suggest 0.7; 0.75 or 0.8 as an appropriate consistency threshold for sufficiency. For sufficient conditions in fuzzy-set Qualitative Comparative Analysis Ragin (2009, p. 118) as well as Schneider and Wagemann (2012, p. 128) suggest a consistency threshold of 0.75. Usually, the consistency threshold for necessary conditions is higher than for sufficient conditions. So as not to draw any wrong conclusions, I apply a consistency threshold of 0.9 for necessary conditions (compare Schneider and Wagemann 2007, p. 213) and 0.75 for sufficient conditions.

    Please keep in mind that * is the logical AND while + is the logical OR in fsQCA notation and ~ marks the inverse value. The results were calculated using the fs/QCA software package (Ragin and Davey 2009).

  7. What might be problematic when conducting a fsQCA for large fiscal stimulus packages is that 22 out of the 30 countries from our sample applied large fiscal stimulus packages. Accordingly, additional research with more refined measures will have to be performed to determine the robustness of the results in light of the classification underlying the calibration of the outcome.

  8. Concerning the treatment of the logical remainders the “Standard Analysis” option of the fs/QCA program of Ragin and Davey (2009) as suggested by Ragin (2008) was applied to derive the parsimonious solution. The most parsimonious solution term is the superset of the paths that form the so-called complex or conservative solution (Schneider and Wagemann 2012, pp. 151–193). 14 out of the 32 theoretically possible conjunctions of conditions are empirically realized. Accordingly 18 logical remainders exist. The Table 4 shows the complex solution.

  9. Some countries in the sample are covered by more than one path of sufficient conjunctions of conditions for large FSPs. In this case, they were reported for each path.

  10. For the Outcome ’Spending-Focused Fiscal Stimulus Package’ ten out of the 16 theoretically possible conjunctions of conditions are empirically realized. Accordingly, there are six logical remainders. The complex solution is as explained in Table 7.

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Authors and Affiliations

  1. Mannheim Centre for European Social Research (MZES), University of Mannheim, A5, 6, 68159, Mannheim, Germany

    Felix Hörisch

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Correspondence to Felix Hörisch.

Additional information

I would like to thank the Fritz Thyssen Foundation for its financial support of this research as part of the project “Partisan Differences, Varieties of Capitalism and the International Financial Crisis: Political Determinants of the Fiscal Political Crisis Reaction of the OECD Member States”. Furthermore, I would like to thank Jakob Weber and the two anonymous reviewers for their very valuable comments.

Appendices

Extent of Stimulus Package (F)

This condition measures the extent to which a country belongs to the group of states that invested broadly in a fiscal package during the economic crisis. The calibration is based on the sum of all responses to the crisis in terms of spending measures or tax revenues.

OECD Data

Total 2008–2010 net effect on fiscal balance in percentage of GDP in 2008

(OECD 2009, p. 62)

Fuzzy-Calibration for the Analysis

F

−8.2 % <national score < −0.8 %Ireland, Hungary, Iceland, Greece

0

0 % <national score < 1 %Italy, Switzerland, France, Portugal

0.33

1.1 % <national score < 6.2 %Poland, Norway, Austria, Slovak Republic, Belgium, Mexico, UK, Netherlands,

Czech Republic, Germany, Finland, Sweden, Denmark, New Zealand, Spain, Luxembourg, Canada, Turkey, Japan, Australia, USA, South Korea

1

Spending-Focused Stimulus Package (S)

This condition measures whether or not a stimulus package of a country in the sample focused on fiscal spending.

Calibration for Countries with Positive Fiscal Stimulus

OECD Data

Total 2008–2010 net effect on fiscal balance in percentage of GDP in 2008: spending(OECD 2009, p. 62)

Fuzzy-Calibration for the Analysis

S

Less than 25 % of the package consist

of spending measuresUK, Finland, New Zealand a,

Czech Republic

0

Less than 50 % of the package consist

of spending measures

Austria, Canada, Luxembourg, Slovak Republic,

Germany, USA, Netherlands, Sweden

0.33

More than 50 % but less than 75 % of the package consist of spending measuresTurkey, Norway, Spain, Mexico, Poland, South Korea, Switzerland

0.67

More than 75 % of the package consist

of spending measuresFrance, Denmark, Australia,

Belgium, Japan, Italyb


1

Portugalc

–

  1. aNew Zealand decided to implement public spending cuts worth 0.3 % of its GDP while investing into tax revenues worth 4.1 % of its GDP. Therefore New Zealand is the only country in the sample that combined spending cuts with a generally positive fiscal stimulus
  2. bItaly planned to implement higher taxes (amounting to 0.3 % of the Italian GDP) to finance equally large spending measures. I argue that its fiscal package should therefore be classified as a generally positive, spending-focused fiscal stimulus
  3. cThe only information that the OECD has provided is that Portugal spent 0.8 % of its GDP on a fiscal package. There is no information on the exact composition of the FSP (OECD 2009, p. 62)

Calibration for Countries with a Negative Fiscal Stimulus

OECD DataTotal 2008–2010 net effect on fiscal balance in percentage of GDP in 2008: spending(OECD 2009, p. 62)

Fuzzy-Calibration for the Analysis

S

More than 75 % of the budget cuts concern spending measures

Hungary

0

More than 50 % but less than 75 % of the budget cuts concern spending measures

0.33

More than 25 % but less than 50 % of the budget cuts concern spending measuresIreland

0.67

Less than 25 % of the budget cuts concern spending measures

Greece, Iceland

1

Government Party-Ideology (P)

This condition models cabinet compositions in 2008 according to the Schmidt-Index ranging from 1 “hegemony of right-wing (and center) parties” (Armingeon et al. 2011, p. 3) to 5 “hegemony of social-democratic and other left parties” (Armingeon et al. 2011, p. 3). In case of a coalition of right-wing and left-wing parties, the party providing the prime minister was crucial. Accordingly, I categorized cabinets as rather left (0.6) or rather right (0.4). All corresponding alterations from my part were marked in bold. The calibration is based on CPDS3-data (Armingeon et al. 2011).

CPDS3 Data

govparty

Cabinet composition (Schmidt-Index) in 2008

(Armingeon et al. 2011, p. 3)

Fuzzy-Calibration for the Analysis

P

1

Denmark, USA, Canada, Greece, Japan, Sweden France

0

2

Switzerland, Finland, Poland, Belgium, Czech Republic, Ireland, Italy

0.33

Left-right coalition with right-wing leader

Netherlands: Jan Peter Balkenende (CDA)

Luxembourg: Jean-Claude Juncker (CSV)

Germany: Angela Merkel (CDU)

Iceland: Geir Haarde (Independence Party)

0.4

Left-right coalition with left-wing leaderAustria: Alfred Gusenbauer (SPÖ)

0.6

4

Norway, Slovak Republic, Hungary,

New Zealand

0.67

5

UK, Spain, Australia, Portugal

1

South Korea, Mexico, Turkey

–

Coordination of Economy (K)

This condition reflects the extent to which a country belongs to the group of states with coordinated market economies. The calibration is based on Hall and Gingerich’s index of economic coordination which ranges from 0 to 1. Scores for countries not classified by Hall and Gingerich were added based on my own assessment due to missing comparable data for these countries (countries marked in bold).

Data by Hall and Gingerich 2004 and added scores

Coordination Index

(Hall and Gingerich 2004, p. 14)

all others marked as bold

Fuzzy-Calibration for the Analysis K

0 ≤national score ≤ 0.25

Canada, UK, USA, New Zealand

0

0.25 <national score ≤ 0.5

Australia, Ireland, Iceland, South Korea, Mexico, Turkey

0.33

0.5 <national score ≤ 0.75

Switzerland, Belgium, Denmark, Finland, France, Japan, Netherlands, Portugal, Spain, Sweden,

Czech Republic, Greece, Hungary, Luxembourg, Poland, Slovak Republic

0.67

0.75 <national score ≤ 1.0

Germany, Italy, Norway, Austria

1

Changes in Central Governmental Debt (D)

This condition reflects the extent to which the countries in the sample experienced a drastic change in their central governmental debt during the crisis years of 2007–2009. The calibration is based on the difference between the scores of the central governmental debt in percentage of GDP in 2007– as provided by the OECD—and the scores from 2009 (OECD 2011).

Data from OECD“Total central government debt % of GDP“ (difference between 2009 and 2007)

(OECD 2011)

Fuzzy-Calibration for the Analysis

D

−3 % <national score < 3 %(Switzerland, Sweden, South Korea, Australia)

0

4 % <national score < 9 %(Germany, Poland, Slovak Republic, Austria, Finland, Turkey, Luxembourg, New Zealand, Mexico, Czech Republic, France)

0.33

9 % <national score< 20 %(Belgium, Denmark, Canada, Italy, Hungary, Portugal, Netherlands, Norway, Spain, USA, Greece)

0.67

26 % <national score < 64 %(Ireland, UK, Iceland)

1

(Japan)

–

National Public Debt in 2008 (B)

This condition measures the extent to which the countries in the sample experienced drastic public debt (including debts of federal states and lower administrative levels) during the crisis year of 2008.

CPDS1-data for 2008“Gross government debt (financial liabilities) as a percentage of GDP”(Armingeon et al. 2010, p. 10)

Fuzzy Calibration for the Analysis B

14 % <national score < 25.5 %(Australia, Luxembourg, New Zealand)

0

39.5 % <national score < 57 %(Denmark, Finland, Switzerland, Spain, Sweden, Ireland, Norway, UK)

0.33

65.5 % <national score < 76 %(Netherlands, Austria, Germany, Canada, USA, Portugal, France)

0.67

93 % <national score< 172.5 %(Belgium, Iceland, Greece, Italy, Japan)

1

(Hungary, South Korea, Mexico, Poland, Turkey, Slovak Republic, Czech Republic)

–

Openness of the Economy (O)

This condition measures the degree to which the countries in the sample can be categorized as open economies in 2007. The calibration is based on CPDS1-data (Armingeon et al. 2010).

CPDS1 Dataopenc“Openness of the economy in current prices, measured as total trade (sum of import and export) as a percentage of GDP” (Armingeon et al. 2010, p. 9)

Fuzzy Calibration for the Analysis O

29 % <national score < 41.5 %(USA, Japan, Australia)

0

55 % <national score< 75.5 %(UK, France, New Zealand, Greece, Italy, Spain, Canada, Portugal, Norway)

0.33

81.5 % <national score< 110 %(Iceland, Finland, Germany,

Sweden, Switzerland, Denmark, Austria)

0.67

142.5 % <national score< 313 %(Netherlands, Ireland, Belgium, Luxembourg)

1

(Slovak Republic, Turkey, South Korea, Czech Republic, Hungary, Poland, Mexico)

–

Change in Unemployment Rates from 2007 to 2009 (U)

This condition measures the degree to which the countries in the sample were affected by a drastically negative development of their unemployment rates during the crisis years from 2007 to 2009. The calibration is based on the difference between the unemployment rate in 2007– as provided by the OECD—and the unemployment rate in 2009 (OECD 2011).

OECD Data“Harmonised unemployment rate: all persons, Level, ratio or US$ million” (Armingeon et al. 2010, p. 9)

Fuzzy Calibration for the Analysis U

−1.5 % <national score< 0.45 %(Poland, Germany, Netherlands,

Austria, South Korea, Belgium)

0

0.60 % <national score < 1.4 %(Norway, Switzerland, Slovak Republic, Luxembourg, France, Greece, Australia, Japan, Czech Republic, Finland)

0.33

1.5 % <national score< 2.7 %(Portugal, Italy, Mexico, Sweden, Canada, UK,Denmark, New Zealand, Hungary)

0.67

3.7 % <national score< 9.8 %(Turkey, USA, Iceland, Ireland, Spain)

1

Change in the National Gross Domestic Products between 2007 and 2009 (G)

This condition measures the degree to which the countries in the sample were affected by a drastically negative change in their national Gross Domestic Products during the crisis years from 2007 to 2009. The calibration is based on the difference between the GDP data (in percent) in 2009 and 2007 as provided by the OECD.

OECD Data“GDP (expenditure approach), US $, constant prices/PPPS, OECD base year”(difference between 2009 and 2007 in percentage)(OECD 2011)

Fuzzy Calibration for the Analysis G

−1.1 % <national score < – 0.5 %(Ireland, Finland, Italy, Japan, Denmark, Hungary, Sweden, Iceland)

0

−0.29 % <national score < 0 %(UK, Mexico, Turkey, Germany, Spain, USA, Portugal, France, Luxembourg, Netherlands, Canada, Austria, Czech Republic, Belgium, Greece, New Zealand, Switzerland)

0.33

0 % <national score < 0.25 %(Slovak Republic, Australia, South Korea

0.67

National score = 0.69 %(Poland)

1

National Trade Union Densities in 2008 (T)

This condition measures the degree to which the countries in the sample exhibited a high trade union density in 2008. The calibration is based on CPDS-scores from 2008. The national labour force scores were divided by the national net union membership to derive the trade union density score. Based on these values, the condition was calibrated as follows:

CPDS-Data for 2008“Civilian labour force, in thousands”

(Armingeon et al. 2010, p. 12)divided by“net union membership (gross minus independent workers, students, unemployed or retired members).”(Armingeon et al. 2010, p. 14)

Fuzzy Calibration for the Analysis T

0 % <national score < 20 %(Australia, Portugal, Germany, Poland, Netherlands, Hungary, Japan, Spain, France, Switzerland, USA)

0

20 % <national score < 40 %(Italy, Canada, Greece, Ireland, UK, New Zealand, Czech Republic, Austria)

0.33

40 % <national score< 60 %(Norway, Luxembourg, Belgium)

0.67

60 % <national score(Iceland, Denmark, Sweden, Finland)

1

(Slovak Republic, Mexico, South Korea, Turkey)

–

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Hörisch, F. Fiscal Policy in Hard Times: A Fuzzy-Set QCA of Fiscal Policy Reactions to the Financial Crisis. Z Vgl Polit Wiss 7, 117–141 (2013). https://doi.org/10.1007/s12286-013-0152-y

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