The effects of IMF conditional programs on the unemployment rate
Introduction
The International Monetary Fund (IMF) has become an almost universal financial institution, with its membership rising from 44 states in 1946 to 190 at present. The basic conception of the IMF's role is to uphold global financial stability, and it is often considered as the “crisis manager” for developing and developed countries. With its loan programs the IMF promoted policy reforms, such as the privatization of state-owned enterprises, trade and financial liberalization, economic deregulation, social policy, labor market reforms, and ‘good governance’, able to restructure the domestic economy of borrowing countries (Kentikelenis et al., 2016). Previous studies highlight that IMF loan programs can have multi-level effects on borrowing countries, including their growth rates (Barro and Lee, 2005; Dreher, 2006), poverty and income inequality (Oberdabernig, 2013; Forster et al., 2019; Lang, 2021; Stubbs et al., 2021; Chletsos and Sintos, 2022), labor rights (Lloyd and Weissman, 2002; Reinsberg et al., 2019), tax revenue (Crivelli and Gupta, 2016; Reinsberg et al., 2020), public spending (Rickard and Caraway, 2019) and health outcomes (Forster et al., 2020).
A strand of literature highlights the impact of international financial institutions (IFIs) on labor (Blanton et al., 2015; Martin and Brady, 2007; Nooruddin and Vreeland, 2010; Vreeland, 2002). Previous work points out that these organizations have notoriously sought to increase the “flexibility” of labor markets – that is, increasing employers' ease in hiring, firing, or setting working hours (Burgess, 2010, p.202) – in borrowing countries, with the promise of future economic growth. Furthermore, previous studies examine the link between IMF programs and labor rights. While Abouharb and Cingranelli (2007) and Blanton et al. (2015) conclude that IMF programs significantly reduce both individual and collective labor rights, Reinsberg et al. (2019) demonstrate that collective labor rights increase in the wake of IMF programs. In this context, studies also examine the effects of IMF program on the public sector. Research results on the effects of IMF loans on public spending are mixed and depend on the sample used and estimated procedure (e.g. Bulír and Moon, 2006; Clements et al., 2013; Kentikelenis et al., 2015; Nooruddin and Simmons, 2006; Nooruddin and Vreeland, 2010). More specific results are reported in Rickard and Caraway (2019), who find that the implementation of reforms related to the public sector to a country's IMF program reduces government spending on the public sector wage bill. Li et al. (2015) point out that IMF policy reforms often lead to an inactive business investment, poorer government service, severe social instability, and a higher unemployment rate – all of which may damage the economic development of bailed-out countries in the long term. The IMF also promotes policies to reduce external and domestic arrears by imposing restrictions on available sources of credit (Kentikelenis et al., 2016). These monetary and debt measures typically lead to higher interest rates, increasing the cost of borrowing and making it more expensive for businesses to expand (Beck et al., 2008; Chletsos and Sintos, 2021a; Marques et al., 2017), which in turn may affect the creation and destruction of private sector jobs. Moreover, previous research documents that IMF conditionality has adverse effects on a range of labor related indicators, including employment levels, wages and employment protection policies (Lloyd and Weissman, 2002; Blanton et al., 2015). Pastor (1987) and Vreeland (2002) empirically investigate the impact of IMF programs on the labor share of income and show that IMF programs are linked to a decline in labor's share of income. In addition, Ohanyan and Androniceanu (2017) show that IMF participation decreases the level of employment using a combination of propensity score matching with the differences-in-differences estimator for the EU-28 between 1993 and 2013. Arguably, the IMF through its policy reforms can alter the underlying structure of an economy, including the labor market (Reinsberg et al., 2019; Chletsos and Sintos, 2021b). Therefore, we focus our attention on labor market issues, and specifically on the level of unemployment.
Should we care about unemployment? During the last century, unemployment has been considered one of the most important factors behind the rise in poverty (e.g. Corcoran and Hill, 1980; Osinubi, 2005; Saunders, 1990). Furthermore, the level of unemployment is linked to various health outcomes. An increased level of unemployment is associated with several mental health issues, such as mixed symptoms of distress, depression, anxiety, psychosomatic symptoms, subjective well-being, and self-esteem (e.g. Backhans and Hemmingsson, 2012; Björklund and Eriksson, 1998; McKee-Ryan et al., 2005; Paul and Moser, 2009). There is also evidence that unemployment increases mortality rates and suicidal behavior (e.g. Córdoba-Doña et al., 2014; Gerdtham and Johannesson, 2003; Lundin et al., 2010; Platt, 1984). Moreover, previous research points out that unemployment increases alcohol consumption and drug use (Henkel, 2011). In addition, several studies show that there is a causal positive relationship between unemployment and both property and violent crime (Lee and Holoviak, 2006; Lin, 2008; Papps and Winkelmann, 2000; Raphael and Winter-Ebmer, 2001). All of these suggest that unemployment is damaging for those who experience it.
In this paper, we explore the influence of IMF programs on the unemployment rate. In exchange for low-cost financing, the IMF requires governments to implement a set of reforms, known as conditionalities (Dreher, 2009). IMF's structural adjustment involves a series of reforms in sensitive policy areas, such as privatization of state-owned enterprises, trade and financial liberalization, economic deregulation, social policy, labor market reforms, and ‘good governance’ (Kentikelenis et al., 2016). These required structural adjustments designed by the IMF to its borrowers can affect the labor market and in turn the unemployment rate of recipient countries. Our study follows the recent strand of the literature (e.g. Forster et al., 2019; Kern et al., 2019; Reinsberg et al., 2021; Stubbs et al., 2020), by investigating both the effect of IMF program participation and conditionality. Most studies treat IMF programs as homogenous (e.g. they include only a binary indicator to capture IMF program participation) and are therefore unable to distinguish specific pathways via which IMF programs affect the outcome of interest. Moreover, to account for the endogeneity bias related to the IMF participation decision and the conditions attached to IMF loans, we follow a recently developed econometric technique (Stubbs et al., 2020), by estimating a system of three equations including instrumental variables via maximum likelihood and allowing for correlated errors across equations (Roodman, 2011).
To account for the aforementioned challenges, this study meticulously assesses the impact of IMF loan programs (conditional on their mandated policy reforms) on the unemployment rate using annually compiled panel data for a world sample of countries between 1980 and 2014. Our baseline findings show that IMF program participation significantly increases the unemployment rate of recipient countries. Once we control for the number of conditions, however, we find that only IMF conditions have a detrimental and highly significant effect on the unemployment rate. In addition, we show that IMF conditions have detrimental long-term implications for the unemployment rate. A more detailed analysis identifies adverse effects on the unemployment rate for four policy areas: labor market deregulation, reforms requiring privatization of state-owned enterprises, external sector reforms stipulating trade and capital account liberalization, and fiscal policy reforms that restrain government expenditure. Our initial results are robust across various specifications.
The rest of the paper proceeds as follows. Section 2 describes the potential pathways through which IMF programs affect the unemployment rate. In Section 3, we discuss the relationship between IMF programs, labor market institutions, and unemployment. Section 4 analyzes our data and the empirical methodology used. Section 5 reports the results. Finally, Section 6 concludes.
Section snippets
Pathways through which IMF programs affect the unemployment rate
We posit two basic pathways linking IMF programs to the unemployment rate. IMF policy reforms – conditions that force countries to implement a series of reforms in order to access IMF credit. The other one refers to IMF operations outside of the conditionality channel.
First, labor conditions that explicitly require dismissal decisions in the public sector can increase the unemployment rate of borrowing countries. Examples abound: Honduras' program in 1994 required the “reduction of employment
IMF programs, labor market institutions and unemployment
Since the beginning of its lending programs, the IMF has suggested that labor market deregulations increase employment and reduce unemployment (Howell, 2005). The IMF has specifically argued that the causes of high unemployment can be found in labor market institutions (e.g. IMF, 2003, p. 129); these institutions are crucial to countries’ labor markets since they can absorb macroeconomic shocks, improve competitiveness and prevent a persistent rise in unemployment (Nickell and Layard, 1999).
Data
We examine the relationship between IMF conditional programs and the unemployment rate using time-series cross-section analysis at the country level over the period 1980–2014. Appendix Table A1 lists all countries included in the study. The sample includes both program and non-program years, as well as countries with no participation in IMF programs. As in most empirical studies, our panel is unbalanced (i.e., there are missing values for some years and countries within the sample period).
Baseline results
Table 1 presents the results of our quantitative analyses on the unemployment rate on five variants of our model. To ensure our model specification is appropriate, specification in column 1 includes only the control variables and is estimated using simple OLS. Services (% of GDP) (p < 0.01), KOF index (p < 0.01), financial crisis (p < 0.01) and elections (p < 0.05) are positively correlated with the unemployment rate. In addition, levels of democracy and economic crisis are associated with
Concluding remarks
In this paper, we provide an empirical investigation on the impact of IMF conditional programs on the unemployment rate using a world sample over the 1980–2014 period. Our baseline findings indicate that IMF program participation significantly increases the unemployment rate of recipient countries. Once we control for the number of conditions, however, we find that only IMF conditions have a detrimental and highly significant effect on the unemployment rate. There is evidence that the adverse
Authorship contributions
Michael Chletsos: Supervision.Andreas Sintos: Conceptualization, Methodology, Software, Data curation, Validation, Formal analysis, Investigation, Resources, Writing - Original draft preparation, Writing - Reviewing and Editing.
Ethical approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Funding
This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme « Human Resources Development, Education and Lifelong Learning» in the context of the project “Strengthening Human Resources Research Potential via Doctorate Research” (MIS-5000432), implemented by the State Scholarships Foundation (ΙΚΥ).
Declaration of competing interest
Michael Chletsos declares that he has no conflict of interest. Andreas Sintos declares that he has no conflict of interest.
Acknowledgements
We especially thank the journal's editor Professor Jan-Egbert Sturm and three anonymous referees for their very constructive remarks and suggestions. We also thank Thomas Stubbs and Timon Forster for their valuable comments and suggestions. Andreas Sintos would like to acknowledge financial support from the IKY foundation. This paper is a part of Sintos' Ph.D. thesis. All remaining errors are our own.
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