The impact of capital account liberalization on the labor share of income
Arjun Jayadev
February 2004 Preliminary Draft, please do not quote without permission
Abstract:
What are the effects of capital account liberalization on distribution? This important topic has been relatively neglected, given the very vocal concerns of many that openness can lead to profound consequences for the personal and factor distribution of incomes. This paper attempts to address this question by asking: what are the direct and indirect effects of capital account liberalization on the labor share of income. I use a consistent cross country panel of labor shares and a new index of capital account openness to test the various channels by which theory suggests that financial openness may affect the labor share. I find a persistent negative effect of capital account openness on the labor share of income across countries and in typical sub samples. The finding is consistent with the idea promoted by Crotty and Epstein ( 1996) and Rodrik ( 1998) that openness may reduce the bargaining power of labor and thereby reduce its share of national output.
In the last few years, the seeming consensus among the world’s elite policy making institutions as to the immediate desirability of a liberal financial regime has somewhat dissipated. Very recent statements from the International Monetary Fund suggest that the expected benefits of open financial markets in terms of increased growth and reduction in macroeconomic volatility have not materialized1. Many researchers, however, maintain the eventual desirability of an open regime, and much effort is now focused on the theoretical and empirical details of less easily tangible and measurable long-run efficiency enhancements (such as increased financial depth, developing legal environments and institutional changes) arising from free capital flows (Levine (2001), Chinn and Ito (2002)). As Cobham (2000) has noted however, the debate around capital account liberalization has centered on a single locus: its potential and realized growth effects. Other crucial standards of evaluation, particularly those of the distributive consequences of capital account liberalization and its entailments on the well being of the poor, have been largely seen as secondary2. This is a somewhat surprising omission on a few counts. First, one of the main charges of numerous critics of the Washington consensus has been precisely that open regimes can worsen income distribution and the condition of the working class and the poor. Second, these topics have been more closely explored in numerous studies dealing with trade openness. Finally, one of the signal changes in the global macroeconomic framework over the last two decades has been the significant increase in cross border capital flows,
This paper seeks to address one aspect of this gap by asking: what can be said about the effects of capital account liberalization on factor shares, and particularly on the labor share of income? This is a slightly different question from that traditionally taken up by the literature on distributional effects. Most economic research on the topic has focused on factor prices: increasing wage and income dispersions arising from various measures of globalization (Wood (1995), Choi (2002), Galbraith (2000)). By contrast, this paper approaches the issue from the older tradition of political economy3, and seeks to assess how various groupings (in particular, labor) are affected by open financial markets.
One of the most difficult problems associated with a cross country study of financial openness is obtaining a useful measure of openness. In this paper I use a new dataset of financial openness developed by a colleague and myself which addresses and overcomes some of the most severe limitations of the extant indices. The problems associated with current measures and the details of the construction of our index are presented in the section on data.
1 “The main conclusions are that, so far, it has proven difficult to find robust evidence in support of the proposition that financial integration helps developing countries to improve growth and to reduce macroeconomic volatility.” Eswar Prasad et al ( 2003).
2 See, for example- Cobham 2000
3 From the classical political economy viewpoint (for Ricardo for example), factor shares were crucial to understanding distribution. If society was stratified according to socially relevant groupings and there was relatively little class mobility between these, the functional distribution of income was a reasonable proxy for the size distribution of income, or at least had a direct relationship with it.
Why factor shares?
Using a factor share approach has some theoretical advantage. The linkages between financial/ real openness and factor share are more easily drawn out then are considerations of interpersonal income distributions. Just as crucially, the approach addresses in a direct way the concerns articulated by Epstein and Crotty (1995) and Rodrik (1997) among others. In an era of structural adjustment and increased global competition, deregulation of international and domestic capital markets may have profound implications for political accords between labor and capital; specifically, by lowering the leverage that labor, the relatively less mobile factor, has. The labor share of income should reflect this process.
In addition, there is the fundamental question of reliable data. Most research directly addressing the question of inequality in a global context has tended to look at size distribution measures such as the gini coefficient and (less often) income shares, from the Deininger and Squire (1999) panel data set or the World Income Inequality Database (2000). Unfortunately, however, there are numerous, and by now well known, problems with these measures. Apart from the sparseness of data for developing and some developed countries, there are difficulties in cross country compatibility of surveys, in analyzing dispersion measures based on consumption versus income surveys, in the underreporting of capital income and so on. Consequently, almost all research using these data has been inconclusive, or severely contested. The heated debates about the effects of globalization on personal income distribution (Milanovic (1999), Sala-I- Martin, (2002)) and on poverty (Ravallion (2003), Bhalla (2002)), suggest that robust conclusions are very difficult to draw from household survey data in a cross country context . Similar debates using the same data (for example on the relationship between inequality and growth (Forbes 2000, Barro 2000, Bannerjee and Duflo 2002)), put forward the same inconclusive results4. By contrast, there are two regularly published and mostly internally consistent datasets for looking at the labor share of income, the United Nations National Accounts Statistics Database and the United Nations Industrial Development Organization’s Survey of Manufacturing.
It is certainly true that looking at factor shares forms just one part of the puzzle as to the overall distributive effects of financial openness and that there are many reasons why functional share effects and personal distributional effects might diverge5. Equally, there are many reasons to believe that capital account openness may impact the size distribution of income through other channels than factor shares. For example, a rise in equity and land prices following inflows may disproportionately benefit those with
3 Perhaps the counsel of Bannerjee and Duflo (2002) is the most instructive in this regard. They maintain that the severe econometric problems associated with these data “….serve as a broader warning against the automatic use of linear models in settings where the theory does not necessarily predict a linear or even a monotonic relationship.”
5 Atkinson ( 1997) lists these as: Heterogeneity of Incomes, Human Capital, Diversity of Sources of Income, Intervening Institutions, and the Impacts of the International and State Sectors. significant assets, causing a greater dispersion in income inequality. Nevertheless, the labor share of income or more generally, the productive structure of the economy may have implications for personal distributional outcomes as well. Pikkety ,Postel-Vinay and Rosenthal ( 2003), for example, finds that one of the most important factors in equalizing personal incomes in France over the last century was the imposition of a significant wealth tax. Similarly Rodriguez (2000) finds that much of the persistence of inequality in Venezuela over the last 40 years can be explained by the large and persistent share of capital’s share of national income.
A simple bivariate pooled cross-country regression suggests that the labor share of income ( as defined by the compensation of employees to GDP from the United Nations National Accounts Data) still has some claim to be correlated with the size distribution of income ( as measured by the high quality gini coefficient data from Deininger and Squire). This is reported in the table below and illustrated in figure (I). Controlling for the level of development (by real gdp per capita), a higher labor share is associated with a more equal and less volatile personal distribution of income ( lower gini6), as might occur if broad societal accords and norms on inequality prevailed.
Dependent Variable: Gini coefficient Compensation of -33.26808 Employees/GDP (-8.36)*** Number of observations 362 Adjusted R2 .227 F 59.61
6 The gini coefficients are restricted to the high quality observations from the Deininger and Squire dataset and those observations listed as acceptable quality in the WIDER database Figure (I) Gini Coefficient and Labor Share
60 50 40 ginidns/Fitted values 30 20
0 .2 .4 .6 .8 1 compensation of employees to gdp ginidns Fitted values
Although using labor shares in empirical work is uncommon, there have been at least three recent papers (Diwan , (2001), Harrison (2002) and Rodriguez (1999)) which have used it for similar purposes. For this paper, perhaps the most relevant reference here is the work of Harrison (2002) who uses National Accounts data to show that there is a correlation between certain standard measures of globalization and a decreasing labor share of income. Harrison’s work is an exercise in assessing the determinants of labor share of income. This paper will seek to build on her work, but focus more heavily on the relationships and channels whereby capital account liberalization in particular may work to affect labor share
The remainder of this paper is structured as follows. In the first section, I begin by detailing the literature on financial openness and the channels by which it may affect the labor share of income. I provide some empirical evidence for the existence of these channels by the use of simple bivariate regressions using the improved measure of capital account openness. I then go on to an empirical subsection wherein I analyze the results from a cross-country panel data analysis, using a specification which allows the testing of the independent and intermediated effects of capital account liberalization on the labor share of income . The final section provides a summary of the results as well as an evaluation of the findings and the potential ways to proceed in further research.
Section (I)
Effects of Financial Openness and Potential Projected Effects on Labor Share of Income: Theory and Evidence
In the recent past, the distributional outcomes of capital account liberalization have become a field of greater research (Diwan (2000), Calderon and Chang (2001), Harrison (2002), Das and Mohapatra (2003),). These papers begin to evaluate the seminal work by Quinn (1997a, 1997 b), which, while clearly implicating capital account openness as correlated with increasingly inequitable distribution, does not specify the mechanisms by which these occur7.
The most obvious linkage between labor shares and processes of globalization arise from consideration of the Heckscher –Ohlin model. With increased openness (whether financial or real), countries with relatively higher endowments of labor would specialize in labor-intensive production, and would see an increase in employment and the labor share of income. Since this prediction is based on competitive commodity trade and immobile factors wherein trade serves as a substitute for factor movements, it follows that the result must hold in the presence of factor mobility. Rodriguez (1999) provides a model arriving at exactly this result. We should broadly, therefore, see a decrease in labor share in the North and an increase in labor share in the South following capital account openness in both regions.
Proponents of financial openness suggest that a major benefit of financial openness is its positive effect on financial deepening (Levine 1997). There is a potential two fold effect that arises from this. First, with a deeper financial market, financing constraints may be eased. As a consequence, financial opening should accelerate accumulation and the absorption of labor and more inward capital flows could ease the finance constraint on smaller, higher employment firms. As such, we should expect an increased labor share of income arising in the short medium run from capital account liberalization in capital scarce, developing countries.
Many economists have studied the possibility of macroeconomic volatility arising from increasing international exposure. Both theoretically and empirically, there has been much effort spent on identifying the links between financial openness and financial crises; and more recently, between financial crises and their distributional effects. Some of these look to capital account openness and the role of lending booms in setting the stage for such shocks (Palma 1998). Kaminsky and Reinhart (1999) support such a view, finding that capital account liberalization immediately preceded crisis in 18 of 22 cases. Another regionally focused cross-country study by Gavin and Hausmann (1996) further bolsters the argument by arguing that lending booms have almost always preceded banking crises in Latin America. Finally, Gourinchas, Valdes and Landerretche (1999)
7 Quinn sees this relationship as arising from the political stance of the state or as a general convergence to the mean verify this finding for a different sample of countries. This view of irrational lending booms is contrasted against other studies such as Caprio and Klingebiel (1996a and 1996b) and Edwards (2004) who find no robust correlation of a link between lending booms and capital account liberalization on financial crises. It is not clear, immediately why this difference arises except in so much as to suggest that each regional banking crisis may have had different proximate causes.
What effect might instability have on the labor share? Weisskopf ( 1979) speaks of the defensive power of labor during downturns in the economy, wherein labor is able to maintain its share over rents because of the institutional features of bargaining in the economy. This would suggest that in downturns, labor share not subject to severe reversals. By contrast, more recent papers in a cross country context, such as Diwan ( 2001) show that financial crises are associated with large negative impacts for labor vis -a -vis capital8. Country specific analyses (for eg. Yeldan 2002) bolster this finding.
A crucial aspect is the effect of financial openness on bargaining between labor and capital. Rodrik, (1997), in his book “Has Globalization Gone Too Far” describes the bargaining game between capital and labor in which increased mobility of capital in the age of globalization increases its bargaining power, and thus its share of economic rents.Reddy (2000) provides a model showing how openness can affect the elasticity of demand for labor, making the demand more elastic, thereby reducing the bargaining power of labor. Similiarly Richardson and Khripunova (1996 ) provide the same logic. Harrison ( 2002) provides a model whereby capital account openness changes the relative bargaining position between capital and labor to the detriment of labor. Slaughter ( 1996) provides evidence of an increasing elasticity of demand for labor following financial opening. Choi (2004) provides a theoretical model and empirical findings which suggest that ‘threat effects’ due the increased mobility of capital in a globalized financial system work so as to reduce the wage premium to unionized labor in the U.S
Among the most potent effects of capital account liberalization are its effects on international price variables. Specifically, openness to capital flows has consequences for the real interest rate and for the real exchange rate. Following liberalization of capital flows, one may expect that the ability of governments to repress interest rates is lost, as capital can gain higher returns elsewhere. Honohan (2000) surveys the effects of financial liberalization on interest rates and finds a consistent and persistent increase in interest rates following the adoption of a more liberal policy. The effects of this on the labor share of income are ambiguous. Clearly rentiers gain from a higher real interest rate ( see Epstein and Jayadev, 2004 for an analysis of this effect in OECD countries), but the effect for the labor share depends on the prevailing political power of non financial capital. That is to say, using a broad returns- to- factor approach, and to the extent that
8 Specifically, Diwan finds that during financial crises, the labor share of income drops 5 percentage points during the financial crisis, and remains below its average by 2.6 percent in the 3 subsequent years. This is a dramatic fall from the average level of 47 percent of the labor share in output. As he puts it: “labor is not simply a bystander that is hurt unintentionally by financial crises, but rather, .. temporary changes in distribution can be a means by which labor partially bails out capital, and thus plays an important role in resolving financial crises”. ( Diwan 2001- page 1) real interest rates are extracted from operating surplus, the relative effect of higher interest rates may squeeze profits or wages, depending on the relative power of labor and non financial capital. A regime of higher interest rates can thereby exacerbate contestation over (more slowly growing) output9.
Finally, there is the claim that capital account liberalization may work to prevent expansionary policy. That is the process of financial opening might involve a subtle but powerful change in national priorities. At one level the government must maintain foreign investor confidence, imposed by the ‘ faceless gnomes’10 of open financial markets, but cannot easily maintain its commitment to other constituencies, including public sector employees. Labor shares are partly driven by changes in government spending and government intervention in the economy in general This is especially so for developing countries in which the governments share of formal employment is typically higher than in developed countries , and often larger than in the private sector (because of the presence of formal unions). Thus, to the extent that government expenditure in the economy is constrained therefore, one would expect to see a fall in the labor share of income.
These arguments are summarized in Table (1).
Table 1: Some hypothesized channels between financial openness and labor share
Positive linkages between Negative linkages between Ambiguous linkages between CAL and Labor Share CAL and Labor Share CAL and Labor Share
1.CAL leads to a rise in 1.CAL reduces the 1.CAL may lead to the capital-labor ratio, bargaining power of labor instability and crisis. The and in the case of and hence reduces the labor effect on labor share imperfect substitutability share of income depends on the defensive between capital and 2. Following CAL power of labor in labor, results in a rise in government intervention downturns labor share . This and spending is 2. CAL increases interest financial deepening constrained by international rates which have unclear also reduces financing financial markets. This effects on the Labor Share constraints on high reduces labor share to the employment, small scale extent that government firms sector exhibits a high labor share
9 Capital account liberalization also has ambiguous effects on labor share through the effects it has on the exchange rate. To the extent that capital flows into developing countries and away from developed ones, the resulting appreciation of the exchange rate penalizes the relatively labor intensive export sector, thereby reducing labor’s share. However, these effects are tempered by both real side trade sector changes, as well central bank policies, which may choose to intervene in the market to adjust exchange rates in keeping with macroeconomic policy.
10 to invoke the phrase used by Thomas Friedman (1999)
Table (II) below presents simple bivariate regressions to test the presence of these effects in developing countries, developed countries and the whole sample respectively. The purpose here is not to make complete specifications of these effects, but rather to assess whether there is an empirical basis in the cross country data to support these conjectures. The table provides some evidence for the validity of these channels, though, it may be noted, these effects vary widely between developed and developing countries.
Capital account openness increases budget surpluses (reduces budget deficits) in developing countries, but reduces them in developed countries. As such, to the extent that capital account liberalization binds expansionary policy, the effect is felt more in developing countries. This finding bolsters the results of Woo (2000) among others who find strong evidence that openness is associated with decreasing budget deficits in developing countries. Similarly, capital account openness is associated with a decrease in capital per worker in developing countries, and an increase in the same variable for developed countries. This simple negative correlation provides some evidence to question the notion that capital account openness leads to capital deepening, and to increased capital accumulation11. There is little evidence that capital account openness is associated with increased financial depth (as proxied by liquid liabilities to GDP)12.
Interestingly, it appears as the effect of capital account openness on financial crises depends on the definition of crisis. Following the rubric of Frankel and Rose ( 1996) who define a financial crisis as occurring when the external value of the currency falls by 20% in a year, capital account openness is associated with lower crises in developed countries and the sample as a whole. It should be noted that these data do not include the East Asian, Russian or Argentinean financial crises for reasons of data availability. Including these episodes would surely strengthen the positive correlation between openness and crises in developing countries. In contrast to this methodology, following Glick and Hutchison’s definition of crisis (either a currency crisis or a financial crisis or both, Glick and Hutchison(1999)) we find a significant positive effect of openness on crisis. This contradiction reflects the ambiguity in the literature as to the relationship between capital controls and crises. As Eichengreen ( 2001) points out, the imposition of capital controls during a crisis often leads to the wrong conclusion that capital controls caused the crisis. All this said, it is probably undisputed that opening up capital accounts does have serious destabilizing potential, at least in the short run. Finally, since it is next to impossible to obtain a proxy for the bargaining power of labor, we do not include it in the table.
11 Morrissey and Baker (2003) provide some evidence that developing countries as a whole are not net importers of capital To the extent that capital account liberalization facilitates flows, these findings are consistent. 12 This non effect remains the case when we use other proxies for financial depth ( M2 to GDP, Deposits to GDP and so on).
Econometric Specification:
In order to test these hypotheses, a panel data estimation with the following specification is undertaken
LSit=αi+βX1it+β2X2it+β3X3it +εit………….(i)
Where the vector X1 refers to a set of controlling macroeconomic and structural indicators, X2 refers to the indicator of capital mobility, and X3 refers to the indicators of the channels by which we may expect capital account liberalization to affect labor’s share of income. If our hypotheses given above are correct, the specification allows us to utilize the correlation between the indicator for capital mobility X2 and the channels through which it operates, X3. That is, if the effects of capital account openness on the labor share work primarily through the channels, elaborating the model by controlling for X3 should reduce the strength of the coefficient for X2, or even make it insignificant.
The results from this specification are detailed in section (III). Before that, it is necessary to outline some important features of the data being used.
Section (II)
Data
Measuring Financial Openness
Most efforts to identify the presence of capital account restrictions have relied primarily on the annual publication of the IMF “Exchange arrangements and Exchange restrictions” which provides details on various regulations on capital account transactions across countries. It has represented the central source for various constructions of financial openness (Quinn 1997, Rodrik 1998, Levine and Zervos 1998, Kraay 1998, Klein and Olivei 1999, Levine 1999, Edwards 2000 , Reinhart and Montiel 2000, Chanda 2001, Harrison (2002), Chinn and Ito 2003). Because of the difficulty inherent in the data, these studies have constantly faced the problem of distinguishing relative degrees of openness, and have come up with various responses, ranging from an outright ignoring of the problem (i.e. treating it as a binary indicator) to providing various remedial measures13. Quinn’ s (1997) index remains the definitive study in this regard. Quinn codes the intensity of capital controls in 7 statutory restrictions on a two point scale and produces an index from zero to fourteen. However, these data are only available for non- OECD countries for 4 years. For the purposes of this paper, we reproduce the methodology, slightly modified utilized by Quinn for his analysis of capital account restrictions and apply this to all the countries in the IMF annual report for the period 1972-1996. While there are substantial evaluative judgments to be made regarding the
13 Kraay (1998) for example distinguishes only between major periods of change ( 5 years of controls followed by 5 years of no controls). qualitative nature of the report, we find that our coding has a .97 correlation coefficient with Quinn’s index for OECD countries and a .91 correlation for the 2 years in the period for which he provides data for all countries. The details of the coding methodology can be found in the appendix.
Figure 1 below details the movements in capital account openness over the last two and a half decades using this indicator. Openness has increased in all groups of countries, with the early nineties being the period of rapid opening up by the poorer groups.
Figure 1: Increasing Capital Account Openness 4 High Income Countries
3.5
3 Upper Middle Income Countries
2.5 All Countries
2 Lower Middle Income Countries 1.5 Low Income Countries Capital Account Openness Account Capital 1
0.5
0 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
One of the advantages of obtaining an indicator of intensity of liberalization is the ability to distinguish between rapid and substantial changes in the capital account regime between countries. Figure 2 shows that rapid and radical opening of the capital account in ten countries14 ( measured as a change of more then 1 in the index over a given period) is associated with large falls in the labor share of income and this effect decreases with the degree of gradualism in the policy.
14 Argentina, Costa Rica, Romania, Trinidad, Ireland, Iceland, Kenya, Peru and Finland Figure (2)
Losses to Labor following rapid capital account liberalization
0.00% Change>1 in Change>1 Change> index in 1 in in index three years -1.00% index in in two one year years
-2.00%
-3.00%
-4.00%
-5.00% years- labor share in year of liberalization of year in share labor years-
-6.00% Change n Labor's share ( Mean labor share in 3 following following 3 in share Mean labor ( share Change n Labor's
Measuring labor shares
In examining factor shares, the main variable of interest that I focus on is the labor share of income. Two data series are utilized for this purpose. The first is one constructed from the national accounts data of the United Nations that covers over a 100 countries from 1960-200015. The UN provides a table of cost components of Gross Domestic Product from which one can derive labor’s share as compensation of employees as a fraction of GDP or of National Income. The second series is narrower, focusing on industrial data collected by UNIDO for over 100 countries over the period 1970-1999. The series representing labor’s share is more direct here, and is given by the ratio of wages and salaries to value added. As such, it is a measure of the labor share of income in manufacturing. The purpose of using this latter measure is three fold. First, it acts as a check on the results obtained in the analysis of the overall labor share. Second, many of the predictions of the effects of open financial markets are on tradeables, and in particular, manufactures. Finally, and perhaps most importantly, it is a measure of the effects on the private economy (all units surveyed are in the private sector). As such, it allows for a rough distinction between the distributional effects of capital account openness in the private sector and in the overall economy (including the public sector)
A few points of caution about the UN data need to be noted. The national accounts data are based on the System of National Accounts 1968, and as such a systematic comparison to other datasets are not possible. However, Harrison (2002) suggests that a relevant
15 Thanks to Christof Paparella for the extension of the data beyond 1997 comparison with the UNIDO data appears to allay fears of inconsistent reporting. Gollin (2002) and Poterba (1997) flag another problem. They both note that the earnings of self- employed persons are not included in the series and as such, their earnings are falsely considered as accruing to capital16. Harrison (2002) shows that while such a maneuver reduces the variation in Labor Share, there is still substantial movement in it, as opposed to the assumptions of a Cobb-Douglas or any other CES function. Finally, and perhaps most crucially, a severe problem arises from the presence of an (often large) informal sector in developing countries. Given that quality data about this sector is by nature impossible to get, the labor share may be underestimated in our data set. This is especially important as many researchers have pointed out that structural adjustment policies (of which capital account liberalization if often a part) often results in a movement to small-scale subsistence agriculture and informality. Presumably the ultimate effect on distribution in countries undergoing capital account liberalization will depend on the relative impact on this sector, especially in the effects of foreign direct investment (and less so in terms of portfolio flows). This is not traditionally theorized in standard models, and the theoretical literature which does consider the effects of globalization and liberalization on the informal sector (Rao, 1995) concludes that overall effects depend very much on the degree of complementarity and competition between the informal sector and the formal sector and thus the impacts will depend on this relationship in different countries17.
Control and channel variables
In assessing the impacts of capital account openness on the changing labor share of income, the question of production technology is crucial. It can be shown that if the elasticity of substitution between labor and capital is not perfect (i.e not equal to 1), then the relative endowments of capital and labor have an effect of labor share. Specifically, higher capital – labor ratios should be associated with higher labor shares. Thus, an implicit assumption is that countries display production technologies which allow for imperfect elasticity of substitution18. While this is ultimately an empirical matter, there are no consistent cross country measures for whether this is the case, and measures of substitutability have varied within country ( Tan 2002, Antras 2003, Rodriguez 1999) . This said, in perhaps the most comprehensive cross country study on the elasticity of substitution, Rowthorn (2000) finds that apart from the United States, most countries
16 Gollin uses a cross section to show that Bowley’s Law (i.e. the relative stability of labor share of income) is retained if the returns to the self-employed are included. 17 Taylor (1988) similarly argues that following liberalization as interest rates rise, funds available will be diverted out of the informal sector to the formal sector. This diversion of credit may not have a net positive impact on employment generation in the formal sector. High transactions costs and risks associated with small loans, a lack of collateral and an historical orientation towards larger enterprises, continue to restrict small-scale formal enterprises access to formal credit. Thus, the effect of capital account and financial liberalization in drawing out the capital from the informal sector into the formal sector (if in fact this is what happens), would not necessarily involve much new employment generation and may in fact have a net deleterious effect on labor share. 18 Another implicit assumption we make is that the supply of labor is not infinitely elastic. That is to say, there are no hidden reserve armies of labor.
exhibit an elasticity of substitution far less than one, suggesting that in general with development and with capital accumulation, there should be a rise in labor shares.
In addition to the fact that one may expect to see rising labor shares because of capital accumulation with development, labor shares may be rising because of what can be termed a Kravis- Kuznets process. Both Kravis ( 1965) and Kuznets ( 1966) emphasize the process of development and structural change as the major reason behind the increase in wage ratios to GDP. Both these authors point to crucial structural shifts in the economy as being central to the process. Some of these are: a movement of labor away from agriculture into a position of wage labor (thereby reducing the proportion of the self- employed), demographic changes and urbanization (which increase the average age of retirement and women’s participation) and the development of organized labor. Given that we expect labor shares to rise with development, and the concomitant rise in capital- labor ratios, we control for this with log ( real GDP per capita). The variable GDP per capita19 is obtained from the Penn World tables 6.1.
Data on the channel variables (the real interest rate, the government share of GDP, the budget surplus , the capital per worker ratio and the nominal exchange rate) are from the World Development Indicators , the IMF international financial statistics and the Penn World tables. As a measure of financial depth, we use the ratio of liquid liabilities to GDP from Beck, Demirguc-Kunt and Levine (1999). From the discussion above, we expect a negative effect on budget surplus and government share on GDP and a positive effect from the capital to labor ratio.
Section (II) Descriptive statistics, estimation results and discussion
The stability of the proportion of the national dividend accruing to labor is one of the most surprising yet best –established facts in the whole range of economic statistics J.M Keynes ( 1939)
19 Other studies use a direct measure of capital stock by labor force, by dividing labor force data from the World Bank by capital stock from Nehru and Dhareshwar (1995). Using real gdp per capita in constant dollars allows for more observations, in particular for developing countries. Figure 3 (a) and (b)
Labor Share By Income Level 55% 1972-1977 1977-1982 1982-1997 1987-1992 1992-1997 1997-2000
50%
45%
40%
35%
30% CompensationEmployees of toGDP
25%
20% Low Income Countries Middle Income Countries High Income Countries
Labor Share Trends Across Countries 70%
United States 60%
Japan
50%
40% Saudi Arabia
30%
CompensationEmployees/GDP of 20% Nigeria
10%
0%
2 6 4 8 68 80 94 960 964 972 978 986 990 1 196 1 1966 19 1970 1 1974 197 1 19 1982 198 1 1988 1 1992 19 1996 199 2000 Year
Quicker Growing Countries See Increases in Labor Share
0.4%
0.3% 0.3%
0.3%
0.2%
0.2%
0.1%
0.1%
0.0% Average GrowthRateLabor of Share Least Quickly Growing Quartile Most Quickly Growing Quartile
-0.1%
-0.1% -0.1%
-0.2%
Figure 3 c The relative constancy of the labor share has been one of the important ‘stylized’ facts of macroeconomics. Commentators as varied as Keynes (1939), Kaldor( 1961), and more recently Mankiw(1993) have suggested that this is the case. By contrast Kuznets (1966) and Kravis (1965) have challenged this notion, suggesting that there is a long term upward trend in the labor share of income. Approaching the data from a less Anglo- Saxon perspective, we find some evidence for the latter position. First, developing countries have a lower labor share than developed countries, although over the last 15 years there has been a secular decline in the labor shares in all countries. We find substantial variation in the labor share of income in our data set across countries, and a general upward trend in the labor share of income for faster growing countries. These are illustrated in figure 3 a -3c. Figure 2a shows the average labor share across country by income levels, over five 6 five- year periods beginning in 1972. Figure 3 b shows the relative constancy of the U.S labor share and the significantly different trajectories of the labor share in Korea, Nigeria and Saudi Arabia. Figure 3 b shows that there is, on average, an increase in the labor share of income in countries developing more quickly. All of these broadly support the Kravis-Kuznets thesis.
Estimation Specification and Results
Table (I) details the time trend of the variable in various groupings of countries. In keeping with the graph 3 (a) above, there is a significant negative trend in the labor share of income in all specifications. Similarly, factor endowments, as proxied by the log of real gdp per capita, also enter significantly in all specifications. This variable accounts for a large part of the variance in the sample. Turning to capital account openness, at the first instance, a striking result is seen. On average, capital account openness exerts a significant and negative effect on the labor share of income. This conclusion differs from the finding of Harrison, for whom capital controls only matter when interacted with general government intervention. A potential reason for this difference may be precisely the fact that the indicator used here takes into account the intensity of controls.
The results also show however, that the obvious ways whereby one may expect this result of inhere (by increasing the potential for crisis and by restricting government spending) are not significant transmission channels. Crises enter the model with a negative sign in most instances, but they do not change the coefficient of capital account openness considerably, suggesting that, while there may be linkages between openness and crises, financial openness exerts an independent negative effect on the labor share. Similarly, a larger government presence, as measured by the government share of GDP, affects labor share positively as does government spending (measured by the budget deficit). Neither of these variables reduces the coefficient on capital account openness, again suggesting that capital account openness has an independent negative effect on labor share. Finally, adding the relative price effects of openness: the real interest rate and the nominal exchange rate into the equation does not mitigate the effect either.
One of the possibilities for this is that capital account openness may be tracking, or partly causing, a reduction in the political power of labor. Harrison (2002 ), Rodriguez(1999) and Reddy(2000) provide differing models to suggest this result whereby financial openness serves to improve the fallback position of the mobile factor( usually capital) and thereby increase capital’s share of income. Certainly, this is a credible story when faced with the numerous indications of these processes in the media and in other academic debates (Rodrik (1997), Bhagwati(1998)).
Given the predictions of standard trade models, we may expect that the effect of capital account openness on labor share is negative in high-income countries, but positive in developing countries. In order to assess this, we repeat the estimation above with a sample restricted to developing countries. The results are given in table (III).
Perhaps most strikingly, while the t statistics on the capital accounts are not as large as with the whole sample, the coefficient on the capital account openness variable remains significant across most specifications, and more crucially, is negative. If anything, capital account openness is associated with falling labor shares in developing countries as well, contrary to a naïve prediction of regression to the mean that may be derived from standard HO theory. While financial openness may not be as dire for labor in the South as in the North, it does exert a downward pressure on labor shares. Another interesting finding is that in the subset of developing countries, one of the channels through which capital account openness affects labor share is by the effect it has on government spending. This is evidenced by the change in the coefficient on capital account openness from column (6) to column (7)20. This bolsters the argument made by Woo(2000). Given the larger proportion of the formally employed in the public sector in developing countries, this makes eminent sense.
Once again, crises affect labor share negatively, but their effect is over and above that of the effect of capital account liberalization. Finally, in this sub sample, introducing real interest rates strengthens the effect on the capital account openness variable suggesting that higher interest rates
Table (IV) reports column(10) for three further subdivisions of the developing country sample into low income, lower middle income and upper middle income countries. As the number of observations drop, the standard errors rise and some variables tend to become insignificant. Nevertheless, it is clear that the basic result, i.e. that capital account openness does not aid labor in the south, as one might expect, holds. In fact, in middle- income countries as a whole, capital account openness is associated with statistically significant losses for labor.
In Tables (V) to (VII) we repeat this exercise with the manufacturing labor share. The effects of capital account openness here are somewhat different. For the whole sample, the coefficient on capital account openness remains negative and significant across most specifications, replicating the results from the economy wide labor share. This does not hold however for the sample of developing countries alone, suggesting that most of the losses to manufacturing labor arising from capital account openness are concentrated in the developed countries. This is itself is not surprising, as evidenced by the decreasing power of labor and labor market deregulation in the North, as well as the outsourcing of manufacturing from developed to developing countries over the last two decades. Capital account openness, however does not lead to concomitant gains for labor in the south, but at least, from this evidence, it does not hurt in most instances. One of the significant channels by which capital account openness may affect outcomes in the manufacturing sector is through interest rates, as evidenced by the large change in sign on the openness variable when real interest rates are added to the specification ( Table V column 7). This might suggest that the interest rate effect of capital account liberalization has a deeper impact on the private manufacturing sector than in the overall economy.
20 A simple check of regressing capital account openness on budget surplus in developing and developed countries further confirms that capital account openness is strongly associated with decreased spending in developing countries, but not in developed countries. This might suggest that the disciplining effect of capital opening on government spending is clearer in developing countries. The five-year averages remarkably similar coefficients for the effect of capital account openness on labor share, suggesting that these effects are not only short term. While in the manufacturing sub sample the effect is not as strong21, it remains significant.
Given that the interpretation of the effect of capital account openness is difficult, table (VIII) reports the standardized coefficients for the overall labor share. The analysis suggests a standard deviation in capital account openness is associated with a .09 decrease in the labor share. This direct effect is about the same magnitude as the effects of changes in the real interest rate and about half that of the effect of a macroeconomic crisis.
Section (III): Conclusions and further research.
This paper sought to assess the conflicting claims made by many as to the distributional impact of opening up capital accounts. Rather than using a de facto measure such as indirect foreign investment, and measuring its impacts, this paper used a relatively developed policy measure to try and tease out changes that may affect labor by altering its political power as well as affect it through market processes. This is important, as some of the central claims made by those who were uneasy with financial openness suggested that the policy was one of a handful which had impacts for social and political accords, and for the ability of government and society to come up with arrangements to maintain standing accords between groups. This clearly has implications for the ability and desire of society to ensure broadly equitable outcomes.
Overall, the results appear to suggest that the fears of labor in the era of globalization are not unmerited. Trade liberalization has direct and concentrated effects on specific sections of labor (often for example, the most protected, the most heavily unionized, the public sector)22. By contrast, Capital Account Liberalization has economy wide effects, changing relative prices of interest rates and exchange rate, precipitating generalized crises (at least in the eyes of some), and perhaps most importantly, negatively affecting the bargaining power of labor as a whole.
The evidence from the use of a more nuanced indicator of capital account openness suggests that this indeed has been the case over the last two and a half decades. Controlling for trends and endowments, and trying various robustness tests, capital account openness is associated with declines in the labor share of income, both in the economy as a whole and within private manufacturing. In some cases, this effect works through some obvious transmission mechanisms. For example, it could be argued that
21 The coefficient becomes insignificant ( but not positive) in all other sub samples ( all developing countries, low income countries, middle income countries and upper middle income countries). 22 Given that Currie and Harrison (1999) find that the pattern of protection in developing countries is towards the most labor intensive, this in itself might suggest some losses for labor following liberalization.
some of the negative effect of capital account openness in developing countries is explained in part by its disciplining effect on government budgets. In most cases and specifications, however, increasing the potential for capital mobility has an independent and negative effect on the labor share of income.
As might be expected from standard international finance models, the opening up of capital accounts globally has the strongest impact in developed countries, with large losses to labor in these countries. The corollary expectation in developing countries, unfortunately for labor in those states, is not usually true. Perhaps most surprisingly, developing countries as a whole also tend to see losses of labor share with capital account openness. Finally, it is also shown that these effects persist through the medium term as well, and the claim that liberalization is simply a temporary shock on labor may not be accurate.
What implications can be drawn from this study? This analysis raises many questions for further scrutiny. Even if capital controls do assist in providing the basis for maintaining factor shares, it is not clear which types of controls may do this. As Jomo, Epstein and Grabel ( 2002) show, countries display a large array of different sorts of controls which defy easy categorization and which are implemented for reasons other than simply egalitarian concerns. Given that the capital account openness measure used cannot be easily interpreted and may be non linear, this issue becomes all the more crucial. Much more research needs to be done on both the types of controls which can help ensure desirably political economy outcomes as well as the various social institutions that need to be in place in order for these to help rather than hinder the development process23.
A second consideration that needs to be highlighted is the existence of a large informal sector in developing countries. While in theory the labor share measure should include this, in practice, by the nature of the problem, this will not be the case. Given that for many countries, this forms the greater part of employment, this is not a trivial omission. Again there is scope and a need to throw light on how this part of the economy responds to and affect macroeconomic outcomes in the face of deep changes.
Finally, there is scant theoretical and empirical work attending to the linkages between financial openness and the size distribution of income or the level of poverty. Allen (2002) in a review of Cobham (2000) proposes that tracing the relationship between capital account liberalisation and poverty is perhaps too onerous a task and that first order relationship may be hard to find. Nevertheless, nuanced case studies may shed some light in the ways in which capital account liberalization interacting with other social processes may affect either positively or negatively, the well being of the poor.
All these concerns listed above can best be addressed by shifting the focus of research to careful country case studies. In fact, the results of this study, as with most cross-country studies, need to be tempered with the acknowledgment that cross country studies may
23 De Long (2001) argues that in the absence of a technocratic elite such as that which existed in the East Asian tigers, capital controls may be detrimental to growth. obscure within-country differences which may be crucial and interesting, but missed in such an analysis. To quote the title of another paper, coming to understand these effects will require going “Beyond Averages”24. This paper provides some evidence to suggest that untrammeled capital account liberalization may be associated with changing factor shares. It is hoped that further case studies provide more evidence and a basis through which countries not yet completely liberalized can assess the desirability of CAL for its overall welfare, including its distributional concerns. As more countries attempt to integrate into a perilous world economy, such research might just provide some indications on how they make this transition in an egalitarian manner.
24 Ravallion (2000)
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Bivariate Regressions with Capital Account Openness ( with country fixed effects and trend variables)
Variable Developing Developed All Countries Countries Countries Budget .72*** -1.0** .12
Surplus (.29) (.4) (.52) Real Interest 3.8*** 1.5** 3.0*** Rates (1.02) (.66) (.6)
Capital Per -200.1* 678.2** 913.1*** Worker (120) (299) (188)
Crisis (I) .08 -.06*** -.05***
(1.5) (.02) (.02) Crisis (II) -.001 .062** .013 (.8) (.03) (.08)
Government -1.25*** -.26 -1.08*** Share of (.24) (.36) (.22) GDP
Liquid -.004 -.008 -.005 Liabilities to (.004) (.01) (.005) GDP
*: Significant at the 10% level **: Significant at the 5% level ***: Significant at the 1% level ( Standard Errors in Parentheses)
Crisis (I): Following Frankel and Rose ( 1996), defined as a year in which the external value of the currency fell by more than 25%
Crisis (II): Following Frankel and Rose ( 1996), defined as a year in which a banking crises occurred, a currency crisis occurred, or both.
Table (I) Time Trend in Labor Shares
Fixed Effect Coefficient on t R-Square N Number of Estimation (T-value in ()) Countries (I) . Economy Wide -.0003 All countries (-3.65) 0.02 2913 141 OECD Countries .0003 0.01 840 23 (3.02) Upper Middle -.0008 0.05 593 25 Income Countries (-3.64) Lower Middle -.0006 0.05 755 40 Income Countries (-2.58)
Low Income -.0026 .01 485 36 Countries (-6.36)
(II) Manufacturing
All countries -.001 (-6.28) 0.001 2793 134 OECD Countries . -.0013 0.024 653 21 (-4.93) Upper Middle .0004 0.01 490 24 Income Countries (1.07) Lower Middle -.0024 0.03 723 37 Income Countries (-7.03)
Low Income -.002 0.02 646 39 Countries (-6.36)
Table (II) All countries, OLS estimation, country fixed effects Dependent 1 2 3 4 5 6 7 8 9 10 11 Variable: Compensati on of Employees /GDP Trend -.003* -.002* -.002* -.002* -.002* -.002* -.002* -.002* -.002* -.003* -.005* (-3.3) (-15.0) (-9.3) (-9.2) (-8.4) (-7.9) (-8.1) (-7.2) (-6.5) (-7.3) (9.7)
Log .078* .064* .058* .053* .056* .064* .085* .082* .069* .07* (Real GDP __ (15.2) (7.8) (7.19) (6.51) (6.82) (7.39) (7.8) (7.3) (6.01) (4.0) per Capita)
Capital -.011* -.009* -.009* -.009* -.009* -.010* -.009* -.007* -.007* Account __ __ (-4.2) (-3.12) (-3.38) (3.31) (3.49) (-3.09) (-3.03) (-3.31) (-3.31) Openness
Current -.001 .0002 .0004 -007** .003 .002 .0004 .0001 Account ______(-0.18) (.06) (0.12) (-2.2) (1.60) (0.6) (0.2) (.25) Restrictions Crisis ______- - -.011* -.001 .012* .014* (-3, -.002 -.001 -.002 (-.23) (-3.6) (-4.0) .5) (-.5) (-.76) (-.74) Government ______.08* . 07** .15* .15* .12* .01* Share of (3.05) (2.46) (4.8) (4.75) (3.05) (3.5) GDP
Budget ______-.003* -.003* - Surplus -.002* -.003* (-10.1) (-9.69) .003* (-7.5) (-9.98) (- 9.69) Real ______.0005* .0005* .0004* .0003 Interest (4.59) (4.56) (3.32) * Rate (3.2)
Exchange ______- - - Rate 0004* 0003* 0002 (-3.33) (-2.64) * (-2.7) Financial ______.063* .061* Depth (5.09) (4.2) Capital Per ______2.2 e6 Worker (3.1) R2 .001 . 0.47 .52 .52 .53 0.55 .56 .59 .63 .64 .64 Obs 2885 2390 1347 1316 1316 1306 1102 803 803 775 483 # of cross 140 117 87 86 86 86 81 73 73 70 46 sections
Table (III) Developing countries, OLS estimation, country fixed effects Compensation 1 2 3 4 5 6 7 8 9 10 of Employees /GDP Trend - -.002* -.002* -.002* -.002* -.002* -.002* -.002* -.002* -.002* .0008* (-13.8) (-7.2) (-7.00) (-6.9) (-5.8) (-5.0) (-5.0) (-2.5) (-2.0) (-6.4) Real GDP per .002* .002* .001* 001* 001* 001* 001* 001* 003* Capita (11.08) (8.4) (7.85) (7.42) (7.6) (7.3) (7.3) (7.3) (6.4) Capital -.012* -.007*** -008*** -.008*** -.006 -.012** -.011** - Account ______(-3.1) (-1.7) (-1.9) (-1.95) (-1.4) (-2.2) (-2.0) .018** Openness (-2.4)
Current 0005 .0015 .001 -.006 -.005 .006 -.006 Account ______(.13) (.34) (.4) (-1.4) (.91) (.12) (-.1) Restrictions Crisis -.017* -.019* -.017* -.002 -.002 - ______(-3.9) (-4.3) (-4.0) (-.4) (-.5) .02*** (-.3.2) Government .125* .168* .28* .26* .13 Share of GDP ______(2.95) (3.48) (4.28) (4.42) (1.43)
Budget Surplus ______-.001* -.003* -.003* -.007* (-4.78) (-6.64) (-6.61) (-10.3) Real Interest ______.0006* .0006* . 0004* Rate (4.41) (4.34) (2.97)
Exchange Rate -.0005* -.0002 ______(-2.37) (-1.06) Financial ______.044 Depth (1.38) R2 .002 .17 .17 .18 .20 .25 .22 .32 .35 0.31 Obs 1805 1486 838 816 816 816 652 429 429 403 # of cross 100 86 62 61 61 61 57 50 50 47 sections
Table (IV) All developing countries, OLS model with fixed effects
Dependent Variable: Low Income Lower Middle Upper Middle Compensation of Employees Countries Income Income Countries /GDP Countries -0.001 -0.002** 0.001 Trend (-1.6) (-2.0) (.79) .00075 0.0037* .000966 Real GDP per capita (.42) (6.4) (2.8) 0.019 -0.018** -0.023** (1.5) (-2.5) (-2.4) Capital Account Openness
0.0027** -0.0069 -0.0089 (1.9) (.1) (-.89) Current Account Restrictions 0.012 -0.023* 0.012 Crisis (1.13) (-3.2) (1.3) 0.60* 0.13 (4.17) (1.2) -0.13 Government Share of GDP (-1.03) 0.0006 -0.007 Budget Surplus (.55) (-10.3) -0.003 (-3.11) 0.001** 0.0005* 0.001 (2.22) (2.97) (3.5) Real Interest Rate -0.00075 -0.00022 -0.00013 Nominal Exchange Rate (-.83) (-1.07) (-1.8) -0.22** 0.044 -0.005 Financial Depth (-2.1) (1.3) (.01) -.00009 -. Capital per worker (3.1) R2 0.07 0.57 0.04 Observations 121 162 120 # of cross sections 16 18 13
Table (V)
All countries, OLS estimation, country fixed effects Dependent 1 2 3 4 5 6 7 8 9 10 Variable: Wages/Value Added Trend -.001* -.001* -.002* -.002* -.002* -.002* -.001* -.003* -.003* -.003* (-6.2) (-7.9) (-5.7) (-5.5) (-5.0) (-5.0) (-2.9) (-4.9) (-4.2) (-4.2) Real GDP ___ .0003* 0005* 0005* 0005* 0005* 0006* 0006* 0005* 0005* per Capita (3.9) (4.0) (4.0) (3.6) (3.7) (4.0) (3.4) (2.8) (2.7)
Capital ______-.011** -.01** -.01** -.01** -.017** -.007 -.007 -.008 Account (-2.8) (-2.5) (-2.6) (-2.4) (-4.0) (-1.5) (-1.5) (-1.6) Openness
Current ______.006 .007 .007 .006 -.012 -.014** -.015** Account (1.12) (1.31) (1.30) (.96) (-1.7) (-2.0) (-2.2) Restrictions Crisis ______-.015** -.015** -.015** -.015 -.015 -.012** (-2.6) (-2.7) (-2.6) (-1.6) (-1.6) (-1.96) Government ______.037 -.08 -.024 -.04 -.04 Share of GDP (.082) (-1.7) (-.4) (-.75) (-.58)
Budget ______-.003* -.003* -.003* -.004* Surplus (-5.65) (-6.5) (-6.6) (-7.0) Real Interest ______Rate .0001 .0002 .0001 (.85) (.97) (.92) Exchange ______-.00004 -.00004 Rate (-2.6) ** (-2.8)** Financial ______.023 Depth (1.1) R2 .002 .25 0.29 0.29 0.29 0.29 .37 .36 .34 .34 Obs 2793 2515 1687 1655 1655 1655 1370 958 958 933 # of cross 134 117 100 99 99 99 93 81 81 78 sections
Table (VI)
All countries, OLS estimation, country fixed effects Dependent 1 2 3 4 5 6 7 8 9 10 Variable: Wages/Value Added Trend - -.001* -.002* -.002* -.002* -.002* -.001* -.003* -.003* -.003* .001* (-7.9) (-5.7) (-5.5) (-5.0) (-5.0) (-2.9) (-4.9) (-4.2) (-4.2) (-6.2) Real GDP .0003* 0005* 0005* 0005* 0005* 0006* 0006* 0005* 0005* per Capita (3.9) (4.0) (4.0) (3.6) (3.7) (4.0) (3.4) (2.8) (2.7) ___
Capital -.01** -.01** -.01** -.01** -.02** -.007 -.007 -.008 Account ______(-2.8) (-2.5) (-2.6) (-2.4) (-4.0) (-1.5) (-1.5) (-1.6) Openness
Current .006 .007 .007 .006 -.012 -.014** -.015** Account ______(1.12) (1.31) (1.30) (.96) (-1.7) (-2.0) (-2.2) Restrictions Crisis ______-.015** -.015** -.015** -.015 -.015 -.012** (-2.6) (-2.7) (-2.6) (-1.6) (-1.6) (-1.96) Government .037 -.08 -.024 -.04 -.04 Share of GDP ______(.082) (-1.7) (-.4) (-.75) (-.58)
Budget -.003* -.003* -.003* -.004* Surplus ______(-5.65) (-6.5) (-6.6) (-7.0) Real Interest ______Rate .0001 .0002 .0001
(.85) (.97) (.92) Exchange ______-.00004 -.00004 Rate (-2.6) ** (-2.8)** Financial ______.023 Depth (1.1) R2 .002 .25 0.29 0.29 0.29 0.29 .37 .36 .34 .34 Obs 2793 2515 1687 1655 1655 1655 1370 958 958 933 # of cross 134 117 100 99 99 99 93 81 81 78 sections
Table (VII)
Developing countries, OLS estimation, country fixed effects Dependent 1 2 3 4 5 6 7 8 9 10 Variable: Wages/Value Added Trend -.001* -.001* -.002* -.002* -0.02* -0.02* -0.02* -.003* -.003* -.003* (-7.3) (-7.6) (-6.2) (-6.5) (-5.9) (-6.0) (-3.6) (-4.6) (-3.8) (-3.4) Real GDP .0006* .0008* .001* .0009* .0009* .0009* .0009* .0008* .0009* per Capita (3.24) (3.11) (3.69) (3.34) (3.86) (4.19) (2.8) (2.4) (2.9) ___
Capital - -.003 -.003 -.002 -.006 -.002 -.001 -.002 Account ______.008*** (-.68) (-.76) (-.43) (-1.19) (-.34) (-.19) (-.34) Openness (-1.68)
Current .02* .02* .02* .01 .003 .003 .003 Account ______(3.3) (3.5) (3.5) (1.5) (.48) (.33) (.34) Restrictions Crisis ______-.018* -.02* -.021* -.014** -.014** -.016** (-2.78) (-2.9) (-2.9) (-1.8) (-1.9) (-2.1) Government .11*8 .03 -.03 -.11 -.09 Share of GDP ______(2.09) (.53) (-.39) (-1.37) (-1.03)
Budget ______-.003* -.003* -.003* -.004* Surplus (-5.3) (-4.7) (-4.9) (-5.3) Real Interest ______Rate .0005** .0005** .0005** (2.05) (2.2) (2.1) Exchange ______-.00007* -.00008* Rate (-4.3) (-4.6) Financial ______-.028 Depth (-.84) R2 .007 0.02 .07 .07 0.09 0.10 0.15 0.19 0.19 0.19 Obs 1859 1697 1155 1126 1126 1126 882 552 552 529 # of cross 100 87 75 74 74 74 69 58 58 55 sections
Table(VIII) All developing countries, OLS model with fixed effects
Dependent Variable: Low Income Lower Middle Upper Middle Wages Countries Income Income Countries /Value Added Countries -0.003** -0.002*** -0.005* Trend (-2.03) (-1.73) (-3.35) 0.0001* 0.0002** 0.000* Real GDP per capita (4.21) (1.9) (4.3) -0.014 0.013 -0.037** Capital Account Openness (-0.88) (1.4) (-2.7)
0.040 -0.006 -0.009 Current Account Restrictions (1.83) (-.56) (-.005) -0.037** -0.003 -0.007 Crisis (-2.45) (-.04) (-.53) -0.44* 0.239 0.55* Government Share of GDP (-3.13) (1.5) (2.77) Budget Surplus -0.004* -0.009* 0.0001 (-3.29) (-5.8) (.003) 0.0001 0.0001*** 0.0001 Real Interest Rate (0.76) (1.7) (.7) 0.0001 -0.0002* 0.0002** Nominal Exchange Rate (1.03) (-5.0) (2.1) 0.144 -0.042 0.037 Financial Depth (1.08) (-.78) (.91) R2 0.09 0.39 0.01 Observations 161 216 152 # of cross sections 21 19 15
Table (IX) Five year averages
Five Year Averages Compensation/GDP Wages/Value Added -0.0028* -0.0039* Trend (-6.15) (-3.8) 0.0822* 0.0649*** Log (Real GDP per capita) (5.11) (1.9) -0.0111* 0.0157*** Capital Account Openness (-2.9) (1.7)
-0.0004 0.0142 Current Account Restrictions (-0.08) (.98) -0.0231** -0.0549* Crisis (-2.57) (-3.1) 0.0018* 0.0002 Government Share of GDP (4.23) (.21) Budget Surplus -0.0013** -0.0028* (-2.44) (-2.6) 0.0008* -0.0003 Real Interest Rate (3.79) (-.58) -0.0001* -0.0001* Nominal Exchange Rate (-3.24) (-4.17) 0.0507* -0.0180 Financial Depth (3.58) (-.6) R2 0.62 .27 Observations 522 633 # of cross sections 53 62
Table (X) Standardized Coefficients OLS regression ( with year dummies)
Dependent Variable: Compensation of Employees /GDP 0.14 Real GDP per capita (2.1) -0.097 Capital Account Openness (-2.1) -0.19 Crisis (-1.96) 0.09 Real Interest Rate (2.5) -0.13 Budget Surplus (-4.2) 0.22 Financial Depth (6.4) R2 .05
Observations 756
# of cross sections 60
Appendix ( I)
An index of capital account openness:
Researchers have long been aware of the problem of using simplistic dummies such as the binary variable from the IMF annual report on exchange restrictions . As a result, some researchers have made efforts to construct continuous measures for the intensity of capital account controls. Among these, the index created by Quinn ( 1997) remains the first, and most popular. Quinn’s index makes careful use of the text of the IMF report to code an index with a value from 0 to 4 with a scale of 0.5.25 He gives each 2 for receipts and payments of international capital flows. His coding rule for capital receipts is as followings and the same decision rule is applied to capital payments.
If approval is rare and surrender of receipts is required, then X=0. If approval is required and sometimes granted, then X=.5. If approval is required and frequently granted, then X=1. If approval is not required and receipts are heavily taxed, then X=1.5. If approval is not required and receipts are not taxed, then X=2 (Quinn, 1997, p. 544.).
Based on this rule, he presents the following example of coding in his paper (Quinn, 1997). Thus, according to him, the capital account restriction has a value of 1 for India in 1979 for example, while the US has a value of 4 and Sweden has 3.
India
Capital: Payment
Residents are prohibited, except with Reserve Bank permission, from engaging in any transaction which increases beyond 49 percent the nonresident share of business outside India … and they are also prohibited, except with Reserve Bank permission, from holding, acquiring, transferring, or disposing of immovable property outside India. … Furthermore, Reserve Bank approval is required for residents exporting Indian securities to any place outside India and transferring Indian securities to nonresidents (IMF 1980 report, p. 196) Indian nationals are not normally granted any exchange facilities fro emigration purposes (p. 197).
Comments: Approval required, rarely granted. Score: 0.5
Capital: Receipts
All proposals for direct investment in India, with or without equity participation, are reviewed by the Foreign Investment Board. … The General or specific approval of the Reserve Bank is necessary for the continuance of commercial, industrial, or trading activities in India or companies incorporated abroad, or with more than 40 percent nonresidents interest (p. 191). [Details of conditions for continuation of business in Indai provided, including equity dilution formulas. pp. 195-61.] In exceptional cases, companies that do
25 Quinn also constructed the index for other restrictions including current account restrictions, exchange rate restrictions and acceptance of IMF article VIII and multilateral agreement to get a composite measure of openness not meet these criteria but have developed skills …, or use technologies not indigenously available, may be permitted a more than a 40 percent foreign participation. … Branches of foreign companies other than airlines, shipping companies, and liaison offices must in all cases become Indian companies (p. 196). Comments: Approval required for all direct investments. Extensive and pervasive indigenous equity requirements. Some “national interest” investments permitted outside guidelines. Score: 0.5
United States
Capital: Payment Incoming or outgoing capital payments by residents or nonresidents are not subject to exchange controls. In addition inward and outward direct or portfolio investment is generally free of any other form of approval (IMF 1980 report. p.424). Comments: Essentially free. Score : 2.0
Capital: Receipts Incoming or outgoing capital payments by residents or non-residents are not subject to exchange controls. In addition inward and outward direct or portfolio investment is generally free of any other form of approval (p.424). Comments: Free. score: 2.0
Sweden
Capital: Payment Direct investment abroad by Swedish residents requires individual authorization, which normally is granted only if the investment is considered likely to promote exports or otherwise to benefit the balance on the current account, regardless of the return on the investment. … Residents do not need authorization to sell portfolio holdings of foreign securities to nonresidents. The purchase of both listed and unlisted securities by residents from nonresidents requires authorization. As a rule, such authorization is not granted (p. 385). Comments: Approval required for direct investments; some capital payments and capital sales permitted. Score: 1.0
Capital: Receipts Foreign direct investments in Sweden require authorization, which normally is given, provided that not more than 50 percent of each individual investment (investments below SKr 5 million excepted) is financed with domestic credit. … Residents are permitted to receive capital receipts from abroad only upon approval of the Rijksbank (p. 384). … Permission is needed for the issuance of bonds and shares in Sweden by nonresidents; bond issues in favor of other Scandinavian countries and [the World Bank] have been admitted (p. 385). Comments: Approval required for all large and many small nonresidents financial activities. Some approvals denied. Score: 1.0 (Quinn, 1997, pp. 541-544).
Although this index is limited in not disaggregated adequately between various types of flows and various taxes on these flows ( a practice that the IMF has begun to take in reports subsequent to 1996), it remains the most reliable. Many recent studies use this index and in doing so suggest that the measure picks up more variation and is more accurate than a simple dummy ( Edwards 2001). Unfortunately, this index is made public only for a select number of years. For OECD countries, the data are available for all years from 1958 to 1997 , while data is available for the rest of the sample only for 1958, 1972, 1982 and 1988. Moreover, the coverage of countries is only 70 countries in total.
In this study, we reconstruct the Quinn-like index, reviewing the IMF report following the same methodology for a large sample of countries.. We use the following coding rule, slightly developed but very similar to original Quinn’s.
If approval is rare and surrender of receipts is required, then X=0. If approval is required in most parts and sometimes granted, then X=.5. If approval is required in some parts and frequently granted, then X=1. If license or any regulation exist in most parts, then X=1. If approval is not required and receipts are heavily taxed, then X=1.5. If approval is required in only few parts and usually granted, then X=1.5 If license or any regulation exist only in a few parts, then X=1.5 If approval is not required and receipts are not taxed, then X=2 If regulation doesn’t exist in almost all parts, then X=2.
This methodology was used to code data from 1972 to 1996 for more than 130 countries in the IMF report. Given that the IMF data is qualitative, we add certain criteria which are available in the report26.
The table below represents the correlation matrix between our measure, that of Quinn and that of the IMF. As can be noted, we have a very high correlation between our index and that of Quinn’s for the OECD countries (.97) and a lower but large correlation between our index and that of Quinn for the non OECD countries. Much of the variation derives from our added criteria.
Quinn IMF Modified Quinn Quinn 1 .67 .97 IMF .67 1 .71 Modifiied Quinn .97 .71 1
26 In addition to Quinn’s criteria, we add some more for to help clear coding. If license is needed and there is regulation in most parts, then we put 1, and if license is needed and there is regulation in a few parts the score is 1.5.