The dependent and control variables included in the analysis belong to one of several categories, namely:
GDP per capita (rgdpl in the WEO dataset, y in this paper): Purchasing power parity (PPP) converted GDP per capita (with the Laspeyres methodology), derived from growth rates of private consumption, government expenditures, and investment at 2005 constant prices.
2) Social conflict indicators
Major cabinet changes (polit11 in the CNTS dataset; CC in this paper): The number of times in a year that a new premier is named and/or 50% of the cabinet posts are assumed by new ministers.
Changes in Effective Executive (polit12 in the CNTS dataset): The number of times in a year that effective control of executive power changes hands. Such a change requires that the new executive be independent of his predecessor.
Coups d’État (polit03 in the CNTS dataset): The number of extra constitutional or forced changes in the top government elite and/or its effective control of the nation’s power structure in a given year. The term “coup” includes, but is not exhausted by, the term “successful revolution”. Unsuccessful coups are not counted.
Major Constitutional Changes (polit04 in the CNTS dataset): The number of basic alterations in a state’s constitutional structure, the extreme case being the adoption of a new constitution that significantly alters the prerogatives of the various branches of government. Examples of the latter might be the substitution of presidential for parliamentary government or the replacement of monarchical by republican rule. Constitutional amendments which do not have significant impact on the political system are not counted.
Legislative Election (polit15 in the CNTS dataset): The number of elections held for the lower house of a national legislature in a given year. A limited number of by-elections are included, but most are not.
Party fractionalization index (polit01 in the CNTS dataset): This index is based on a formula proposed by Douglas Rae (1968), and is constructed as follows:
where ti is the proportion of members associated with the ith party in the lower house of the legislature (where there are no parties, a zero is entered).
In calculating the Index entries, independents are disregarded and legislative changes between elections are not taken into account. It should also be noted that sources vary on the distribution of seats (and even the overall number of seats) for many countries; thus figures calculated by different researchers may vary.
Assassinations (domestic1 in the CNTS dataset). Any politically motivated murder or attempted murder of a high government official or politician.
General Strikes (domestic2 in the CNTS dataset). Any strike of 1,000 or more industrial or service workers that involves more than one employer and that is aimed at national government policies or authority.
Guerrilla Warfare (domestic3 in the CNTS dataset). Any armed activity, sabotage, or bombings carried on by independent bands of citizens or irregular forces and aimed at the overthrow of the present regime.
Major government crises (domestic4 in the CNTS dataset; GC in this paper): Any rapidly developing situation that threatens to bring the downfall of the present regime, excluding situations of revolt aimed at such overthrow.
Purges (domestic5 in the CNTS dataset). Any systematic elimination by jailing or execution of political opposition within the ranks of the regime or the opposition.
Riots (domestic6 in the CNTS dataset). Any violent demonstration or clash of more than 100 citizens involving the use of physical force.
Revolutions (domestic7 in the CNTS dataset). Any illegal or forced change in the top government elite, any attempt at such a change, or any successful or unsuccessful armed rebellion whose aim is independence from the central government.
Anti-government Demonstrations (domestic8 in the CNTS dataset). Any peaceful public gathering of at least 100 people for the primary purpose of displaying or voicing their opposition to government policies or authority, excluding demonstrations of a distinctly anti-foreign nature.
Weighted index of political instability (domestic9 in the CNTS dataset; WI in this paper): This is a weighted conflict measure, with the specific weights for different conflicts being the following: Assassinations (25), Strikes (20), Guerrilla Warfare (100), Government Crises (20), Purges (20), Riots (25), Revolutions (150), and Anti-Government Demonstrations (10).
Adverse regime change (AD in this paper): Indicator (dummy = 1) variable for an adverse regime change episode in the PITF dataset.
The following composite indicators are the result of a principal component analysis (PCA) of several groups of individual indicators. For each composite measure, we choose the first component based on Cattell’s scree plot test:
Principal component indicator of political instability (labeled PC in this paper): Includes the indicators domestic1 through domestic8 from the CNTS dataset.
Composite measure of political instability (JAP in this paper): Includes the measures of political instability obtained by Jong-A-Pin (2009), when the ICRG data are not used.
Furthermore, the following measures (obtained also by PCA) correspond to the groups of indicators suggested by Aisen and Veiga (2013):
Regime instability index 1 (labeled RI1 in this paper): This measure includes the indicators Cabinet Changes (polit11) and Executive Changes (polit12) from the CNTS dataset.
Regime instability index 2 (labeled RI2 in this paper): This measure includes the indicators Cabinet Changes (polit11), Constitutional Changes (polit04), Coups (polit03), Executive Changes (polit12) and Government Crises (domestic4) from the CNTS dataset.
Regime instability index 3 (labeled RI3 in this paper): This measure includes the indicators Cabinet Changes (polit11) and Executive Changes (polit12) … Cabinet Changes (polit11), Constitutional Changes (polit04), Coups (polit03), Executive Changes (polit12), Government Crises (domestic4), Number of Legislative Elections (polit15), and Fragmentation Index (polit01) from the CNTS dataset.
Violence index (labeled VI in this paper): This measure includes the indicators Assassinations (domestic1), Coups (polit03), and Revolutions (domestic7) from the CNTS dataset.
3) Macroeconomic and demographic controls
Price of investment (PI, from PWT): Price level of investment (in logs).
Openness (Open, from PWT): (log) Openness at 2005 constant prices, in percent.
Population growth (Popg, series SPPOPGROW from WDI): Population growth (annual percent rate).
4) Governance and regulation indicators
Governance (WGI, from Kaufmann et al. 2010): Composite measure of the six governance indicators described in Kaufmann et al. (2010): Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption. These indicators are aggregated by means of PCA, from which we choose the first component (with the highest associated eigenvalue).
5) Political indicators
System (DPI, from Beck et al. 2001): parliamentary (value equal to 2); assembly-elected president (1); president (0).
Polarization (DPI, from Keefer and Stasavage 2003): maximum difference between the chief executive’s party’s value and the values of the three largest opposition parties.
Government fractionalization (DPI, from Beck et al. 2001): probability that two deputies picked at random from among the government parties will be of different parties.
Margin majority (DPI, from Beck et al. 2001): fraction of seats held by the government.
Opposition’s share (DPI, from Beck et al. 2001): total vote share of opposition parties.
Autocracy (Polity IV Project): level of government autocracy.
The following indicators are composite measures for the quality of regulations on product and labor markets, provided by the Fraser Institute’s Economic Freedom of the World (EFW) report 2010. The index ranges between 0 and 10, with higher scores being assigned to economies with better (more flexible) regulations:
Business/product markets (area5c, from EFW): Composite index for the quality of business and product market regulations, based on the following sub-components: Price controls, Administrative requirements, Bureaucracy costs, Cost of starting a business, Extra payments/bribes, Licensing restrictions, and Cost of tax compliance.
Labor markets (area5b, from EFW): Composite index for the quality of labor market regulations, based on the following sub-components: Hiring regulations and minimum wage, Hiring and firing regulations, Centralized collective bargaining, Hours regulations, Mandated cost of worker dismissal, and Conscription.
The composite indicator of product market flexibility considered in the analysis is the one provided by the Fraser Institute’s Economic Freedom of the World (EFW) and rates countries between 0 and 10, with higher scores being assigned to economies with better (more flexible) regulations. The indicator is based on the following sub-components: i) Price controls; ii) Administrative requirements; iii) Bureaucracy costs; iv) the Cost of starting a business; v) Extra payments/bribes; vi) Licensing restrictions; and vii) the Cost of tax compliance. The composite indicator of labor market flexibility considered in the analysis is also obtained from the Fraser Institute’s Economic Freedom of the World (EFW) and rates countries between 0 and 10, based on the following sub-components: i) Hiring regulations and minimum wage; ii) Hiring and firing regulations; iii) Centralized collective bargaining; iv) Hours regulations; v) Mandated cost of worker dismissal; and vi) Conscription.
The results obtained estimating equation (3) using the product market flexibility indicator are shown in Figure A1. Looking at the figure, it emerges that the response of output to social conflict over the medium-term is a function of product market flexibility. In particular, the results suggest that seven years after the occurrence of a social instability episode, the contraction in output is about 2 percent larger in countries where product market flexibility has decreased than in countries where flexibility has increased.
Similarly, the results obtained for reforms in the labor market suggest that the response of output to social conflict over the medium-term is also a function of labor market flexibility (Figure A2). However, reforms in labor market seem to be less efficient than reforms in governance and product market flexibility in boosting output over the medium-term. In particular, the results show that in order for medium-term output to be higher than pre-crisis levels, reforms implemented in the labor market have to be of a larger-scale than those in governance or the product market. In addition, while reforms in product market flexibility and governance tend to have significant effects after 5 years of the occurrence of the social instability episode, labor market reforms have significant effects only after seven years.
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See Annex for details.
Real GDP per capita is expressed in constant PPP international dollars of 2005. The maximum in our sample corresponds to Qatar in 2009.
Except for that between the Commonwealth of Independent States and the Advanced Economies, which is -0.03.
This high correlation is not surprising, though, given that CC is used in the construction of RI1.
See Annex for details.
The finite sample bias is in the order of 1/T, where T in our sample is 31.
The two-step system-GMM estimates (with Windmeijer standard errors) are computed using the xtabond2 Stata command developed by Roodman (2009). Social instability and all control variables are considered as endogenous (instrumented using up to 2 lags). The time trend is considered as predetermined. The significance of the results is robust to different choices of instruments and predetermined variables.
Consistency of the two-step GMM estimates has been checked by using the Hansen and the Arellano-Bond tests. The Hansen J-test of over-identifying restrictions, which tests the overall validity of the instruments by analyzing the sample analog of the moment conditions used in the estimation process, cannot reject the null hypothesis that the full set of orthogonality conditions are valid. The Arellano–Bond test for autocorrelation cannot reject the null hypothesis of no second-order serial correlation in the first-differenced error terms.
Assuming that social instability has a negative effect on output, the bias would be negative.
Other political variables which feature prominently in the empirical literature—such as election cycles, political ideology, government fractionalization, measures of political stability, and the presence of a constitutional limit on the number of years the executive can serve before new elections—have been tested but proved to be statistically insignificant.
The Chi-square test of the null hypothesis of joint significance is 13.23, which is higher than the critical value (10) suggested by Staiger and Stock (1997) for strong instruments. The Hansen J-statistics and the Kleibergen-Paap Wald type F-statistics also validate the exogeneity of the instruments.
Given limited data on political variables we were not able to extend the analysis for 6 and 7 years ahead.