محدودیت های اعتباری و سرمایه گذاری در سرمایه انسانی: شواهد آموزشی از اقتصادهای در حال گذار
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|18867||2014||25 صفحه PDF||سفارش دهید||14680 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Financial Intermediation, Volume 23, Issue 1, January 2014, Pages 76–100
Using a unique survey database of 8265 firms from 25 transition economies, I find that lack of access to finance in general, and to bank credit in particular, is associated with significantly lower investment in on-the-job training. This effect is stronger in education-intensive industries and in industries facing good global growth opportunities. To address endogeneity issues, I use the structure of local credit markets as an instrument for credit constraints at the firm-level. In addition, in panel estimates, I control for the presence of unobserved firm-level heterogeneity, as well as for changes in macroeconomic conditions.
It is widely recognized that capital market imperfections can have adverse consequences for firm growth. A large empirical literature has documented the negative effect of credit constraints on capital investment (Love, 2003), R&D investment (Brown et al., 2009), and advertising expenses (Fee et al., 2009), among others. One potentially important alternative channel is investment in human capital through on-the-job training. Firm investment in human capital is costly1 and at the same time intangible, thus harder to finance than physical assets. Becker (1962) was the first to argue that lack of access to external financing may depress efficient investment in training, either because credit constrained workers will not be willing to accept lower wages, or because credit constrained firms may not be able to pay workers more than their marginal product during the training period. However, because direct measures of credit constraints are missing in conventional datasets, there is no microevidence that credit constraints affect training or that the magnitude of the effect is economically important. In this paper, I attempt to uncover the missing link. I use data from the 2005 EBRD/World Bank “Business Environment and Enterprise Performance Survey” (BEEPS) on 8265 small and medium enterprises from 25 transition economies to analyze the impact of various self-reported financing constraints on on-the-job training. The survey contains detailed firm-level information on training, on different proxies for credit access, and on various firm-level characteristics which enables me to control for a variety of standard predictions of human capital theory. Under what conditions should firm-level credit constraints matter for on-the-job training? The theoretical literature provides answers to this question along two dimensions, related to the nature of training and to the structure of labor markets. In traditional human capital theory, firms do not pay for general training whose cost is fully borne by the workers, and so firm-level credit constraints should matter only in the case of specific training (Becker, 1962). More recently, the literature has suggested that firms are willing to pay for general training too, for example because they obtain superior information on the worker’s ability during training (Acemoglu and Pischke, 1998), or because the firm’s monopsonic power results in a compressed wage structure (Acemoglu and Pischke, 1999b). In these models, credit constraints on the side of the firm matter as long as the firm enjoys a certain degree of oligopsonic wage setting power, and as long as contractual problems do not prevent the firm from committing to providing training once the worker has made a wage concession. There are three main stumbling blocks in evaluating the impact of credit market imperfections on investment in human capital. The first one is that while the literature has studied extensively what constitutes a credit constrained firm,2 credit constrained firms are usually not observable. Indirect tests based on the response of wages to training in current and future jobs (e.g., Booth and Bryan, 2005) are unable to reveal the magnitude of the negative effect of credit constraints on training. In contrast to such studies, and similar to Jappelli, 1990 and Cox and Jappelli, 1993, I identify firms that do not have access to credit markets from replies to direct questions about whether firms were denied credit or did not apply fearing that they would be denied. Second, credit constrained firms may also be firms for which the return to training is lower due to their more general technology, to their inability to lock workers into long-term contracts, or to their low degree of oligopsonic power. The detailed firm-level dataset used in this paper allows for separating the effect of credit constraints from the effect of these alternative factors. In particular, I observe how long it takes the firm to fill a vacancy (a proxy for oligopsonic power), the extent to which the firm is subject to labor and social security inspections (a proxy for the degree of contractual problems between the firm and its workforce), and the frequency with which the firm updates its technology (a proxy for the mix of general vs. specific training). The most important stumbling block is that the use of survey-level data raises standard concerns about endogeneity. For one, there is the problem of reversed causality: less efficient (low-growth) firms may be reporting higher financing constraints as they shift the blame for their underinvestment to the country’s credit markets. For two, the cross-sectional nature of the data raises questions about omitted variable bias: for example, unobserved growth opportunities or managerial ability could be the main driving force behind the scale of the firm’s on-the-job training program. If less efficient firms over-state their credit constraints, or if firms with more able managers and with better growth opportunities are also less constrained, then a negative association between credit constraints and on-the-job training will be capturing a simple correlation between the two, rather than a causal link from constraints to training. I address these issues in three ways. First, I employ a difference-in-differences specification whereby I exploit the fact that firms in certain industries are more likely to benefit - in terms of on-the-job training - from relaxed credit constraints. Second, I employ an instrumental variable procedure based on exploiting local variation in credit provision. In particular, I use the structure of local (city-level) credit markets as an instrument for the firm’s credit constraints. Bank competition has been shown to affect small firms’ access to credit positively by lowering the cost of credit to newcomers (Cetorelli and Strahan, 2006). At the same time, it is unclear why credit market structure should affect corporate investment in human capital directly, and so there is no reason to expect that the exclusion restriction would be violated. Third, I identify a subset of firms that were also observed in the 2002 wave of the BEEPS, and employ a fixed effect panel regression in order to eliminate the effect of unobserved time-invariant firm-level heterogeneity. My results suggest that credit constraints have a significant effect on the provision of firm-level training. Problematic access to external finance in general, and inability to access bank credit in particular, is associated with significantly lower investment in training. All else equal, a credit constrained firm has as much as a 9.3% lower probability of running a formal on-the-job training program for its employees than a firm which is not constrained in credit markets. This effect is stronger in industries that employ a relatively more skilled workforce and that face good global growth opportunities. The results survive when I formally control for the main determinants of training suggested by standard human capital theory (Becker, 1962 and Oi, 1983) and by the “new training” literature (Katz and Ziderman, 1990, Acemoglu and Pischke, 1999a and Acemoglu and Pischke, 1999b). More importantly, the main results of the paper survive when I employ an instrumental variable procedure to eliminate possible reversed causality in the cross-section, and in the fixed effects panel regressions where I eliminate the bias induced by unobservable time-invariant firm-specific factors. In that sense, the estimated effects do not appear to be driven by training and financing constraints being jointly determined by various omitted variables at the firm or country level, or by inefficient firms shifting the blame for their underinvestment to the financial system. Additional tests suggest that training is positively correlated with sales growth and that firms cut other costs too, such as capital investment and advertising expenses, in response to adverse credit market conditions. My results thus confirm that lower investment in human capital is just one of several channels through which credit constraints depress firm growth. This study relates to the literature on the real effects of financial market imperfections. Credit constraints have long been shown to matter for capital investment (Fazzari et al., 1988). La Porta et al., 1998 argue that differences in financial systems can explain much of the variation across countries in firms performance. Cooley and Quadrini, 2001 and Clementi and Hopenhayn, 2006 develop theoretical models of borrowing/lending relationships to support the conjecture that borrowing constraints have important implications for firm growth and survival.3 However, while previous studies have pointed to the large negative effects of financing constraints on firm growth (Beck et al., 2005), the literature has mostly focused on the effect of financing constraints and financial development on investment in non-human capital, such as capital investment (Love, 2003) or R&D investment (Li, 2011). This paper is the first to study the channel of human capital accumulation through which financial market frictions may depress firm-level, as well as aggregate, productivity growth in emerging markets. The paper also relates to the empirical literature on the determinants of human capital investment by the firm. Acemoglu and Pischke (1998) provide evidence on the effect of the firm’s informational monopsony power on its incentives to provide general training. Leuven and Oosterbeek (2004) show that tax deductions lead Dutch employers to offer more training. Dustmann and Schonberg (2009) provide evidence on the effect of unionization on training that the firm pays for. Neumark and Wascher (2001) present evidence that minimum wages reduce formal training to improve skills on the current job. Unlike these studies, I test for the effect of credit constraints on training, and my firm-level data allow me to attain numerical estimates of this effect. The paper proceeds as follows. In Section 2, I introduce the data. Section 3 discusses the identification of the causal effect of financing constraints on training. I report the main results in Section 4. In Section 5, I report the results from the tests in which I account for the potential endogeneity of financing constraints. In Section 6, I compare numerically the effect of credit constraints on training to its effect on other type of firm investment. Section 7 concludes.
نتیجه گیری انگلیسی
Theory predicts that investment in on-the-job training is sub-optimal in the presence of capital market imperfections, but data unavailability makes it difficult to distinguish this effect from the effect of firm size, the mix between general and specific training, labor contract rigidities, or oligopsonic wage-setting. I overcome this difficulty by using a unique survey dataset on 8265 firms from 25 emerging markets, which includes replies to questions about actual experience with access to finance, in order to isolate the effect of credit constraints on training. The reliance on firm-level data allows me to achieve a substantial methodological improvement over previous empirical studies: I observe a range of actual credit constraints at the firm level; I observe reliable proxies for the main alternative factors investigated in standard human capital theory and in the new training literature, notably firm size, the training mix, technological opportunities, and labor market characteristics; and I can purge the estimated effect of credit constraints on training from the bias resulting from reversed causality (e.g., inefficient firms exaggerating their credit constraints because they blame credit markets) or from omitted firm-level factors (e.g., unobserved managerial ability driving both training and access to finance). My results indicate that various types of credit constraints are consistently associated with a lower probability that a firm will pay for the training of its employees. This effect survives the inclusion of a wide range of observable firm-level and country-level characteristics, as well as the elimination of factors common for all firms in a market or an industry. Crucially, I employ three different strategies to address concerns about endogeneity. I use a difference-in-differences specification whereby I test whether credit constraints are more detrimental for investment in human capital in industries that are more likely to benefit – in terms of training – from better access to finance. In the cross-section, I employ an IV procedure where I use the structure of local credit markets to extract the exogenous element of credit constraints. In fixed effect panel regressions, I eliminate the effect of unobservable time-invariant firm-level heterogeneity. The main results of the paper survive these procedures. Finally, I find that firms cut other costs too, like capital investment and advertising expenses, in response to adverse credit market conditions, confirming that lower investment in human capital is just one of several channels through which credit constraints depress firm growth. The use of survey data also allows me to calculate the numerical effect of capital market imperfections on investment in training. According to the preferred instrumental variables regression, credit constrained firms have as much as a 15% lower probability of offering training to their employees. My estimates thus allow for a rudimentary calculation of the aggregate effect of credit constraints on training. For example, if firms in Macedonia were on average as unconstrained as firms in Slovenia (Table 1), as many as 7% more firms would be offering training to their employees, explaining around a quarter of the difference in aggregate training between the two countries. The results in the paper thus point to large and insofar not documented benefits - in terms of investment in human capital - from improving corporate access to finance.