Autocracy, Democracy, and FDI Inflows to the Developing Countries

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Autocracy, Democracy, and FDI Inflowsto the Developing CountriesBenhua Yang aa Department of Economics , University of New Hampshire , USAPublished online: 30 Aug 2007.

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International Economic JournalVol. 21, No. 3, 419–439, September 2007

Autocracy, Democracy, and FDI Inflowsto the Developing Countries

BENHUA YANG

Department of Economics, University of New Hampshire, USA

ABSTRACT This paper investigates the relationship between political regimes and ForeignDirect Investment (FDI) inflows to the developing countries for a sample of 134 countriesover the 1983–2002 period. Using two categorical measures of regime type and three differentmeasures of FDI, this study finds that, regardless of the measures of regime type, democraciesare not significantly associated with either FDI in level or FDI as a ratio to GDP; democracy ispositively related to a higher level of per capita FDI, but this result is not robust to alternativemeasures of political regime. Taken as a whole, there is no evidence of a systematic relation-ship between democracy and FDI inflows. This result suggests that being a democracy doesnot help attract higher levels of FDI.

KEY WORDS: Autocracy, democracy, regime, foreign direct investment, developing countriesJEL CLASSIFICATIONS: F21 F23

Introduction

While the impact of Foreign Direct Investment (FDI) on economic growth isstill under intense debate among scholars (e.g. Balasubramanyam et al., 1996;Borensztein et al., 1998; Carkovic & Levine, 2002), many less developed countries(LDCs) have been actively seeking FDI inflows since the early 1980s, based onthe belief that FDI can bring several benefits, including technology transfers,managerial skills and access to international markets. Over the 1983–1992 period,seven out of the ten largest FDI recipients in the developing world are autocracies,but democracies dominate the top-ten list in the 1993–2002 period (see Table 1).The same pattern can be seen when FDI is measured as a share of GDP. In terms of

Correspondence Address: Benhua Yang, Department of Economics, Whittemore School ofBusiness and Economics, University of New Hampshire, Durham, NH 03824, USA. Email:[email protected].

1016-8737 Print/1743-517X Online/07/030419–21 © 2007 Korea International Economic AssociationDOI: 10.1080/10168730601027179

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Table 1. Top ten FDI recipients

1983–1992 1993–2002

China∗ 3.33 China∗ 39.60Singapore∗ 2.72 Brazil∗∗ 17.24Mexico∗ 2.54 Mexico∗∗∗ 12.88Malaysia∗ 1.76 Singapore∗ 9.79Brazil∗∗ 1.42 Argentina∗∗ 7.28Argentina∗∗ 1.28 Poland∗∗ 4.95Thailand∗∗∗ 1.10 Chile∗∗ 4.05Egypt∗ 0.84 Malaysia∗ 3.73Indonesia∗ 0.71 Czech Republic∗∗ 3.68Nigeria∗ 0.63 Thailand∗∗ 3.30

FDI/GDPSt. Kitts/Nevis∗∗ 14.81 Equatorial Guinea∗ 43.32Singapore∗ 9.76 Lesotho∗∗ 17.82St. Lucia∗∗ 8.19 St. Vincent/Grenadines∗∗ 15.53Equatorial Guinea∗ 6.90 St. Kitts/Nevis∗∗ 15.18Dominica∗∗ 6.75 Angola∗ 12.92Seychelles∗ 6.24 Azerbaijan∗ 12.28Swaziland∗ 5.75 Singapore∗ 11.72Grenada∗∗∗ 5.44 Guyana∗∗ 9.88Guyana∗∗∗ 4.72 Grenada∗∗ 9.61Malaysia∗ 4.02 Trinidad/Tobago∗∗ 9.37

FDI per capita ($)Singapore∗ 926.89 Singapore∗ 2578.07St. Kitts/Nevis∗∗ 464.89 St. Kitts/Nevis∗∗ 1054.86Seychelles∗ 230.19 Equatorial Guinea∗ 561.04St. Lucia∗∗ 193.15 Seychelles∗ 547.56Dominica∗∗ 140.27 Trinidad/Tobago∗∗ 482.77Grenada∗∗∗ 113.21 Bahamas∗∗ 414.77Cyprus∗∗ 108.27 St. Vincent/Grenadines∗∗ 407.17Malaysia∗ 98.70 Czech Republic∗∗ 358.44Oman∗ 82.43 Grenada∗∗ 335.82Trinidad/Tobago∗∗ 76.34 Israel∗∗ 334.87

Note: ∗autocracy in the entire period;∗∗ democracy in the entire period;∗∗∗regime changes in the period.Source: World Bank (2004), Cheibub & Gandhi (2004).

per capita FDI, there are five democracies ranked among the largest FDI recipientsin the 1983–1992 period, and this figure has increased to seven in the recent decade.Interestingly, it is also in the recent decade that the developing world has witnessedan explosive increase in the FDI flows. The question is, does being a democracyhelp attract high levels of FDI?

The answer from the existing literature is ambiguous. While some authors(e.g. Li & Resnick, 2003; Jensen, 2003) argue that democracy promotes FDIinflows by providing better property rights protection, others (O’Donnell, 1978;Haggard, 1990; Greider, 1998) argue that FDI favors autocracy for reasons suchas its capacity to suppress labor demands, repress against protesters, and offer taxincentives to the advantage of multinational corporations (MNCs). In the end, it

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Autocracy, Democracy, and FDI Inflows to the Developing Countries 421

appears that the question of whether regime type is systematically related to FDIinflows can only be resolved by empirical investigation.

This paper attempts to empirically examine the relationship between politicalregime and FDI inflows to the LDCs in a systematic way. Using the latest datacovering up to 134 countries, this study finds that, regardless of the measures ofregime type, democracies are not significantly associated with either FDI in levelor FDI as a ratio to GDP; democracy is positively related to a higher level ofper capita FDI, but this result is not robust to alternative measures of politicalregime. Taken as a whole, there is no evidence of a systematic relationship betweendemocracy and FDI inflows. This result suggests that being a democracy does nothelp attract higher levels of FDI.

The current work is related to the literature on the determinants of FDI ingeneral (for a comprehensive survey, see Chakrabarti, 2001) and the small polit-ical economy literature concerning the association between democracy and FDIflows in particular. Since Blonigen & Wang (2004) show that the factors deter-mining the FDI inflows are systematically different between developed versusdeveloping countries, this study draws on the work focused on the LDCs forbaseline specification (e.g. Schneider & Frey, 1985; Edwards, 1990; Jun & Singh,1996; Asiedu, 2002). Closely related to this study is the recent empirical work thatdirectly assesses democracy–FDI connection, which yields contradictory findings.Examining the US FDI to the developing world, Oneal (1994) finds no relationshipbetween political regime and US FDI outflows. Rodrik (1996), Harms & Ursprung(2002), Jensen (2003), and Busse (2004) find that FDI flows are significantly higherin democracies. Resnick (2001) shows that democracy has a negative impact onFDI, yet Li & Resnick (2003) modify this negative relationship by concludingthat democracy may hamper FDI, but it also has a positive impact through bet-ter property right protection. Focusing on the US FDI in Latin America over the1979–1996 period, Tuman & Emmert (2004) find that more repressive politicalregimes received more US FDI.

Almost all of the previous work assesses the influence of regime type on FDIinflows using continuous, ordinal scales of political regime, hence essentiallyexamining the impact of degree of democracy on FDI. By contrast, this studyemploys categorical measures of political regime, thus directly investigating theassociation between regime type and FDI, which is in line with both the theoret-ical arguments and the public criticisms that MNCs favor autocracies. In otherwords, the existing studies answer the question of whether the increased level ofdemocracy leads to more FDI, while this study seeks to answer the question ofwhether regime type has any effect on FDI inflows.

This paper also improves upon the existing work in several other ways. First,while most of the analyses use yearly data, the present investigation employs five-year averages of FDI to minimize the influences of business cycles, hence focusingon the long-run FDI inflows. Second, it looks at the democracy–FDI nexus usingthree different measures of FDI, in level, as a fraction of GDP, and in per capita,therefore distinguishing between different dimensions of FDI. Third, in contrastwith the relatively small sample size used by previous work (e.g. 19 countries inResnick, 2001; 53 countries in Li & Resnick, 2003; 62 in Harms & Ursprung,2002; 69 in Busse, 2004), this study includes up to 134 LDCs, thus promoting the

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422 B. Yang

credibility of the regression results and ensuring that any policy conclusions aremore broadly based.1

The paper proceeds as follows. The next section discusses the theoreticallinkages between democracy and FDI, the third section describes the data andmodel, and the fourth, fifth and sixth sections examine the relationship betweenregime type and FDI using three measures of FDI: level, FDI/GDP, and percapita FDI, respectively. The seventh section discusses the endogeneity issue. Theconclusion is provided in the final section.

The Theoretical Linkages between Regime Type and FDI

It is often argued that FDI favors democracy because democratic regime is ableto provide secure property rights protection. Since there is no guarantee thata state does not violate private property, the constraints offered by democraticinstitutions are essential to make the property rights protection credible (North& Weingast, 1989; Olson, 1993; Bates, 2001). To the extent that violations ofproperty rights including expropriation, contract repudiation, and ineffective ruleof law deter FDI inflows, the provision of effective property rights protection andcontract enforcement by a democracy will promote FDI inflows (Li & Resnick2003; Jensen, 2003). Similarly, Henisz (2000) argues that the higher number ofveto players in the democratic system places constraints on policy changes andhence helps attract FDI.

Despite these arguments, the effect of democracy on FDI inflows becomesambiguous when we look at the issue more closely. Li & Resnick (2003), forexample, argue that the pluralism ensured by a democracy may generate pol-icy outcomes hurting foreign investment inflows, because democratic constraintsmay weaken the monopolistic positions of MNCs, prevent host governments fromoffering financial and fiscal incentives, and provide local business protection fromforeign competition. Furthermore, even the provision of effective property rightsprotection in a democracy comes into question, as it is suggested that the introduc-tion of democracy is not necessarily associated with better protection of privateproperty (Olson, 2000), but often related to property rights violations to securepopular support (Przeworski, 1991). Indeed, it is the long-lasting democraciesthat are more likely to provide secure property rights protection and contractenforcement (Clague et al., 1996). Unfortunately, the majority of long-lastingdemocracies are not seen in the developing world.

On the other hand, a number of authors argue that autocracy is at a betterposition in attracting FDI inflows. For instance, O’Donnell (1978) argues thatautocrats protect foreign investors from pressure for higher wages and high tax-ation. Haggard (1990) suggests that an autocracy can shield political elites fromdistribution pressures, and hence allow them to pursue various economic policies.For autocrats with a long-time planning horizon, even secure property rights canbe provided (Olson, 1993, 2000; Clague et al., 1996); to the extent that property

1Excluding the small states (defined as having average population over the sample period less thanone million, see for example Easterly & Kraay, 2000) does not alter our results. These results arenot reported, to save space, but are available upon request.

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rights protection is positively associated with FDI inflows, stable autocracies areexpected to win higher levels of FDI.

The argument that autocracy helps attract FDI, however, is also debatable.Although there is evidence that autocracies pay lower wages (Rodrik, 1999), theeffect of low wages on FDI inflows might have been over-emphasized (Markusen,1995). For autocracies with longer-time planning horizon, the credibility of prop-erty rights protection ‘is weakened by the fact that their leaders are accountablemerely to the ruling elite and exercise power out of their own volition’ (Li &Resnick, 2003, p. 187). In addition, MNCs are under pressure from many humanrights organizations not to favor autocratic regimes. Therefore, an autocracy isnot likely to enjoy advantages over democracy in competition for FDI.

In sum, the existing theoretical work does not offer a clear direction of therelationship between regime type and FDI inflows to the LDCs, it is thereforenecessary to resolve the issue by empirically investigating the democracy–FDIconnection.2

Data and Model

There are up to 134 developing countries in the study covering the period 1983–2002.3 Following the convention in the growth literature, the traditional non-OECD members are taken as developing countries. A list of the countries coveredis provided in Appendix A.

The dependent variable is FDI net inflows, which has been used in the literaturein at least three ways: level, as a ratio to GDP, and in per capita. The previousfindings are often cited in the literature without making any distinction amongdifferent measures of FDI. Nonetheless, different measures of FDI can have differ-ent implications. Although LDCs are in competition for more FDI and the largerrecipients usually catch the public attention, a higher FDI/GDP ratio might notbe desirable because when this is the case, the issue of dependency and loss ofsovereignty are likely to be raised. In addition, as can be seen in Table 1, whenmeasured relative to GDP and in per capita, the top ten FDI recipients in boththe 1983–1992 and 1993–2002 period are dominated by small states. These twomeasures thus are not quite compatible with our question of whether democ-racy helps attract more FDI inflows to the LDCs. Furthermore, as noted by Li &Resnick (2003), using the FDI/GDP as a dependent variable makes it difficult toseparate the effect of political regime on FDI, as FDI/GDP is obviously influencedby GDP. To answer the question of whether autocracy or democracy receives more

2Chakrabarti (2003) developed a structural model to facilitate empirical studies on the potentialdeterminants of the spatial distribution of FDI. Democracy has no role in his theoretical construct,which is consistent with our later finding that being a democracy does not help a developing countryattract more FDI inflows.3The sample period is chosen for several reasons. First, as noted by Chakrabarti (2001), FDI increas-ingly became a reliable and important source of capital flows for the LDCs after the 1982 debt crisis.Second, many developing countries minimized acts of FDI expropriation, lifted FDI restrictions andstarted actively seeking FDI in the early 1980s, hence using the year 1983 as the starting point mightput them on the ‘equal footing’ in FDI competition. In addition, Li & Resnick (2003) also focus onthe years since the early 1980s.

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FDI inflows, FDI measure in level seems to be more appropriate. Nevertheless,the other two measures are also used in this study to both check the robustnessof the results and make it easier to compare with previous results. The data forthe measures of FDI come from World Bank (2004) WDI.

The variable of interest is regime type. The existing literature concerning theeffect of political regime on FDI typically uses a continuous, ordinal scale ofdemocracy, thus essentially examining the relationship between degree of democ-racy and FDI. To directly investigate the effect of regime type, this paper usesthe categorical measure of political regime from Przeworski et al.(2000) (hence-forth PACL), which classifies a political regime in a country in each year as eithera democracy or a dictatorship. Their classification is strictly based on electoralcontestation. Three basic rules are used to distinguish a democracy from a dicta-torship: (1) the chief executive must be elected; (2) the legislature must be elected;(3) there must be more than one party. For the ambiguous regimes, they employ theadditional ‘alternation’ rule, which applies to the countries that have passed thebasic rules and the incumbent party that had won every election from some timein the past did lose elections. Under the alternation rule, Botswana (1968–1990)is classified as a dictatorship. The PACL measure of regimes is consistent since itexclusively relies on observables rather than on subjective criteria. The originalPACL data set only covers the period 1950–1990, hence this paper uses the versionupdated to the year 2002 by Cheibub & Gandhi (2004).

Although PACL unambiguously identify each country as either a democracyor an autocracy, their classification is often criticized for the narrow definitionof democracy. As a robustness check, this paper also employs the widely usedsubjective measure of democracy from Polity IV (Marshall & Jaggers, 2002) toassess the relationship between political regime and FDI inflows.

The Polity IV database measures the political regime by using the Polity score,which ranges from –10 (strongly autocratic) to +10 (strongly democratic). It iscomputed by subtracting the 11-point Autocracy score (-10 to 0) from the Democ-racy score (0 to 10). Both the Autocracy and Democracy scores, in turn, are derivedfrom a number of component measures, including competitiveness of executiverecruitment, openness of executive recruitment, constraints on chief executive,regulation of participation and competitiveness of participation. To facilitate theuse of polity score in time series analysis, Polity IV introduces a polity2 vari-able in 2002, which converts instances of regime interruption, interregnum, andtransition into conventional polity scores. To transform the polity2 index into acategorical variable, this study first follows the political science literature by usinga (−7, 7) threshold (see, for example, Reiter, 2001), namely, a country is defined asa democracy if polity2 >= 7, an autocracy if polity2 <= −7, and an incoherentregime if it falls in-between. Alternatively, regime type can be defined by using a(−6, 6) threshold (see, for example, Mansfield et al., 2000).

The control variables are chosen from the studies on the determinants of FDIin LDCs (e.g. Schneider & Frey, 1985; Edwards, 1990; Jun & Singh, 1996; Asiedu,2002). Five relatively standard variables are included: GDP based on PurchasingPower Parity (when FDI level is the dependent variable) and GDP per capita as aproxy for market size, real per capita GDP growth, trade openness measured bythe sum of exports and imports divided by GDP, and the number of telephones

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per 1000 people as a proxy for infrastructure.4 The data for these control variablescome from World Bank (2004) WDI. The regime type dummy is next added tothe baseline equation.

In short, the baseline specification takes the following form:

Ln(FDI)it = β0 + β1 ln(GDP)it0 + β2Ln(GDPpercapita)it0 + β3Growthit0

+ β4Openit0 + β5Phoneit0 + β6Democracyit0 + eit (1)

where i indexes countries, t indexes time periods, and t0 indicates the value atthe beginning of a period. FDI takes one of the three measures: level, ratio toGDP, and per capita FDI.5 Three regional dummies, North Africa and MiddleEast, Europe and Central Asia, and South Asia are included in all cases. Theregions are based on the World Bank country classification. Period dummies arealso included when the specification is estimated using the Ordinary Least Square(OLS) estimator for the 1983–2002 period.

For this study, the 1983–2002 period is divided into four sub-periods, eachcovering five years, namely, 1983–1987, 1988–1992, 1993–1997, and 1998–2002.Using averages over the whole period may produce misleading results, since, forexample, the majority of the new states created after the fall of communismhave FDI data available only after 1992, but these countries arrive at the time ofincreased FDI inflows to the developing world, thus may result in higher averageFDI flows over the entire sample period. In addition, there are feedback concernswhen the averages of the independent variables are employed, and use of the initialvalues over a 20-year period as a solution does not seem to be appropriate. On theother hand, FDI inflows may vary considerably from year to year due to factorssuch as business cycle, which makes the use of yearly data undesirable. Therefore,this study adopts the five-year average to better capture the long-run FDI inflows.To minimize the possible feedback from FDI to regime, all of the independentvariables, including the regime dummy, enter the regression using the values atthe beginning of each period.

The specification is first estimated using OLS panel regression, with up to fourobservations for each country. The OLS panel easily takes into account the cross-section as well as the time-series dimension of the data. To take care of the possibleresidual correlation problem, a Seeming Unrelated Regression (SUR) system witha separate equation for each period is also estimated. The SUR technique allowsthe error terms to be correlated across equations. In using the SUR method, thisstudy follows the convention by constraining the slope coefficients to be the same,but the intercept terms to be different across the equations.

4Chakrabarti (2001) confirms the robustness of the correlation between FDI and market-size (asmeasured by per-capita GDP) using Extreme Bound Analysis, and suggests that, among the con-troversial explanatory variables, a country’s trade openness is most likely to be correlated with itsFDI inflows, followed by its wage, net exports, growth rate, tax, tariffs, and exchange rate. Thecontrol variables employed in this study are selected to facilitate comparison with the existingdemocracy-FDI studies.5To prevent negative values due to the use of log, the latter two measures of FDI enter the equation (1)using the form log (1 + FDI).

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The estimation of an unbalanced SUR system (i.e. the equations have anunequal number of observations), however, usually leads to loss of efficiencybecause the equations are required to be balanced. As a number of countries,especially the newly created ones in the 1990s, do not have FDI data in the earlierperiods, these states are often discarded in the estimation process. Moreover, con-straining the parameters of a SUR system to be the same does not appear to beappropriate, as it has been noted that the nature of FDI inflows to the developingcountries might have changed in the 1990s, from resource-seeking and low-wagelocation integrating to market-seeking (OECD, 2004). It is also plausible thatthe behavior of LDCs might have been different in the recent decade. Conse-quently, instead of estimating a SUR for the entire period, two SUR regressionsare estimated, one for the 1983–1992 period and another for the 1993–2002 period.

Regime Type and FDI

We examine the issue of whether democracy is systematically associated withhigher levels of FDI by first looking at the absolute level of FDI inflows. Li& Resnick (2003) argue that this measure is better for answering the questionof whether democracy receives more FDI. The first three columns of Table 2

Table 2. Regime type and FDI (Dependent variable: log (FDI), five-year average)

OLS Panel SUR

1983–2002 1983–1992 1993–2002 1983–1992 1993–2002

Log (GDP) 1.037∗∗∗ 1.054∗∗∗ 1.045∗∗∗ 1.111∗∗∗ 0.957∗∗∗(0.000) (0.000) (0.000) (0.000) (0.000)

Log (per capita GDP) −0.399∗∗ −0.468 −0.297 −0.766∗∗ −0.141(0.035) (0.162) (0.147) (0.030) (0.550)

Growth 0.045∗∗∗ 0.071∗∗∗ 0.032∗∗ 0.057∗∗∗ 0.035∗∗∗(0.000) (0.002) (0.018) (0.002) (0.000)

Trade openness 0.013∗∗∗ 0.018∗∗∗ 0.009∗∗∗ 0.019∗∗∗ 0.004∗∗(0.000) (0.000) (0.000) (0.000) (0.025)

Log (Phone) 0.528∗∗∗ 0.544∗∗ 0.520∗∗∗ 0.721∗∗∗ 0.444∗∗∗(0.000) (0.011) (0.000) (0.002) (0.002)

North Africa/ −1.028∗∗∗ −0.632 −1.482∗∗∗ −0.706 −1.469∗∗∗Middle East (0.000) (0.125) (0.000) (0.102) (0.000)Europe/Central Asia −0.916∗∗∗ −1.591∗ −0.853∗∗∗ −1.207 −0.583∗∗

(0.000) (0.090) (0.000) (0.118) (0.044)South Asia −1.855∗∗∗ −2.088∗∗∗ −1.563∗∗∗ −2.227∗∗∗ −1.630∗∗∗

(0.000) (0.000) (0.000) (0.000) (0.002)Democracy 0.212 0.262 0.082 0.113 0.077

(0.173) (0.377) (0.645) (0.717) (0.679)

Observations 400 161 239 71; 71 115; 115R Squared 0.731 0.658 0.743 0.60; 0.75 0.70; 0.75RESET test (0.629) (0.736) (0.089)Breusch-Pagan test (0.002) (0.000)

Notes: Robust standard errors are used in all cases of OLS regression.Time dummies (in the OLS panel regression for the entire period) and constant terms are not presented.P-values are reported in parentheses. ∗significant at the 10% level.∗∗significant at the 5% level, ∗∗∗significant at the 1% level.

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show the results of OLS panel regressions. Column 1 presents estimation resultscovering the period 1983–2002 (with up to four observations for each country),while Columns 2 and 3 report results for the 1983–1992 and 1993–2002 period,respectively. There are at most two observations for each country in each sub-period. FDI is used in logged term, which easily brings the RESET test into line.The overall fit of the model is reasonable; for instance, it explains about 73% ofthe variation in FDI inflows for the entire period. Consistent with other studies,countries with large GDP, fast growth, higher degree of trade openness, and bet-ter infrastructure are related to more FDI inflows, whereas high GDP per capitais associated with less FDI. When FDI is measured at absolute level, total GDPappears to be a better proxy for market size. The negative sign of per capita GDPdelivers the message that per capita GDP is possibly capturing the effect of laborcost. The estimates of the three regional dummies suggest that North Africa andthe Middle East, Europe and Central Asia, and South Asia attract less FDI relativeto other regions of the world.

The estimates of the democracy dummy are positive but insignificant in allcases, indicating that regime type has little effect on FDI inflows. The OLS panelregression, however, does not take into account the possibility that the error termsmight be correlated. Consequently, a SUR system allowing for residual correlationis estimated. The results of the SUR estimation are presented in Column 4 and5 in Table 2, with Column 4 showing the results for the 1983–1992 period, andColumn 5 for the 1993–2002 period. As can be seen, the positive estimates of thedemocracy dummy continue to be highly insignificant, suggesting again regimetype does not play a major role in attracting FDI inflows.6

Table 3 adds some additional control variables identified in the literature to thebaseline specification (1). These variables include measures of inflation, naturalresource abundance captured by the sum of fuels, ores, and metals export asa share of merchandise exports, measures of life expectancy, and population.The data for these variables are from World Bank (2004) WDI. Inflation servesas a proxy for macroeconomic stability. Natural resource abundance takes intoaccount the fact that FDI in many developing countries is resource-seeking. Thelife expectancy is intended to capture the impact of the population health in thecountry, and the population is an alternative measure of market size and potential.Because measures of resource abundance and life expectancy are quite stable ina short term, like five years, they enter the regressions using period averages. Useof averages for resource abundance also prevents the sample size from shrinking,as the data for a number of countries are missing at the beginning of a period.

As shown in Table 3, these additional variables hardly add much explana-tion power to the FDI differences across countries. There is weak evidence ofa negative relationship between inflation and FDI. Measures of resource abun-dance and life expectancy are positively correlated with FDI, but insignificant.

6The insignificance of the democracy dummy in each sub-period also suggests that there is noevidence of structural break during the sample period in the estimated democracy–FDI relation-ship. Although there are cases indicating a structural break (see, for example, Table 9), this is notsupported by the vast majority of the regression results. For possible structural break around othertime points, it is not clear a priori and therefore not explored in the study.

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Table 3. Regime type and FDI (1983–2002): additional control variables (Dependent variable: log(FDI), five-year average)

OLS panel

1983–2002 1983–2002 1983–2002 1983–2002

Log (GDP) 1.066∗∗∗ 1.081∗∗∗ 1.033∗∗∗(0.000) (0.000) (0.000)

Log (per capita GDP) −0.460∗∗ −0.710∗∗∗ −0.413∗∗ 0.669∗∗∗(0.022) (0.001) (0.029) (0.000)

Growth 0.042∗∗∗ 0.066∗∗∗ 0.046∗∗∗ 0.046∗∗∗(0.004) (0.000) (0.000) (0.000)

Trade openness 0.013∗∗∗ 0.012∗∗∗ 0.013∗∗∗ 0.013∗∗∗(0.000) (0.000) (0.000) (0.000)

Log (Phone) 0.600∗∗∗ 0.734∗∗∗ 0.437∗∗∗ 0.474∗∗∗(0.000) (0.000) (0.000) (0.000)

Log (Inflation) −0.109∗(0.057)

Resource abundance 0.001(5-year average) (0.787)Life Expectancy 0.015(5-year average) (0.115)Log (Population) 1.111∗∗∗

(0.000)Democracy 0.145 0.141 0.192 0.203

(0.366) (0.401) (0.221) (0.198)Observations 369 306 399 400R Squared 0.743 0.732 0.733 0.734Reset test (0.551) (0.181) (0.623) (0.618)

Notes: Regional and time dummies as well as constant terms are not presented.Robust standard errors are used in all cases.P-values are reported in parentheses. ∗significant at the 10% level.∗∗significant at the 5% level, ∗∗∗significant at the 1% level.

The estimate of population, however, is large in magnitude and high in signif-icance level (GDP is not included in this regression due to concern of perfectcorrelation). More importantly, in no case does the democracy dummy becomestatistically significant, consistent with the previous finding of no relationshipbetween regime type and FDI inflows.

It is noted that some countries experienced regime changes in the sample period,and ignoring this fact might affect the estimation results. To test this possibility,the baseline specification is re-run using the average values of regime type. In thiscase, a regime is defined as a democracy if it is a democracy in every year in afive-year period, a regime is an autocracy if it is an autocracy in every year in theperiod, and all others fall into the category of mixed regimes, which involve regimechanges. Table 4 presents the estimation results. As can be seen, the estimatesof the democracy dummy continue to be positive but insignificant. While theOLS panel regression for the entire period indicates that regime changes arenot significantly related to FDI, the results of both OLS and SUR regressionssuggest a significantly negative link between regime changes and FDI inflows

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Table 4. Regime type, regime changes and FDI (Dependent Variable: log (FDI), five-year average)

OLS SUR

1983–2002 1983–1992 1993–2002 1983–1992 1993–2002

Log (GDP) 1.037∗∗∗ 1.057∗∗∗ 1.045∗∗∗ 1.125∗∗∗ 0.953∗∗∗(0.000) (0.000) (0.000) (0.000) (0.000)

Log (per capita GDP) −0.416∗∗ −0.416 −0.386∗ −0.766∗∗ −0.141(0.026) (0.211) (0.057) (0.000) (0.546)

Growth 0.045∗∗∗ 0.069∗∗∗ 0.029∗∗ 0.059∗∗∗ 0.032∗∗∗(0.000) (0.002) (0.018) (0.002) (0.000)

Trade openness 0.013∗∗∗ 0.018∗∗∗ 0.009∗∗∗ 0.019∗∗∗ 0.003∗(0.000) (0.000) (0.000) (0.000) (0.061)

Log (Phone) 0.528∗∗∗ 0.498∗∗ 0.544∗∗∗ 0.631∗∗∗ 0.433∗∗∗(0.000) (0.018) (0.000) (0.008) (0.002)

North Africa/ −1.023∗∗∗ −0.620 −1.432∗∗∗ −0.489 −1.452∗∗∗Middle East (0.000) (0.154) (0.000) (0.264) (0.000)Europe/Central Asia −0.961∗∗∗ −1.715∗∗ −0.921∗∗∗ −1.172 −0.633∗∗

(0.000) (0.045) (0.000) (0.128) (0.029)South Asia −1.797∗∗∗ −2.088∗∗∗ −1.519∗∗∗ −2.477∗∗∗ −1.530∗∗∗

(0.000) (0.000) (0.000) (0.000) (0.002)Democracy 0.247 0.349 0.120 0.452 0.130

(0.119) (0.296) (0.494) (0.182) (0.528)Mixed −0.406 −0.063 −0.695∗∗ 0.562∗ −0.597∗∗∗

(0.130) (0.889) (0.04) (0.090) (0.009)Observations 403 162 241 71; 71 115; 115R Squared 0.739 0.659 0.755 0.60; 0.72 0.73; 0.74Reset test (0.611) (0.714) (0.227)Breusch-Pagan test (0.001) (0.000)


in the 1993–2002 period, which supports the view that the political instabilityassociated with regime transformations could hurt foreign investments.

Is the finding of the no-relationship between democracy and FDI ‘robust’ toalternative measures of regime type? Table 5 presents the answer using the mea-sures of democracy based on Polity IV data. Column 1–3 gives the results obtainedusing the threshold (−7, 7) as a cut-line to define autocracy versus democracy. Ascan be seen, there is weak evidence supporting the claim that democracy is ben-eficial for FDI inflows, since the coefficient of democracy dummy is marginallysignificant (p-value of 0.097) for the entire period. Looking at the SUR estimatesfor the sub-period, we see that this significance largely comes from the 1993–2002 period (p-value of 0.095). Relaxing the threshold to (−6, 6) gives moreobservations of both democracies and autocracies, but the democracy dummyloses significance in the sub-period. Relaxing the threshold further to (−5, 5)yields a similar result. Taken as a whole, there is little support for the claim thatdemocracies are associated with higher levels of FDI inflows.

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Table 5. Regime type and FDI: alternative measure of regime (Dependent variable: log (FDI), five-yearaverage)

Threshold (−7, 7) Threshold (−6, 6)

OLS SUR SUR OLS SUR SUR

1983–2002 1983–1992 1993–2002 1983–2002 1983–1992 1993–2002

Log (GDP) 1.060∗∗∗ 1.065∗∗∗ 1.000∗∗∗ 1.061∗∗∗ 1.067∗∗∗ 1.008∗∗∗(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Log (per capitaGDP)

−0.362∗ −0.735∗∗ −0.172 −0.374∗∗ −0.725∗∗ −0.196

(0.058) (0.041) 0.482 (0.050) (0.046) (0.422)Growth 0.050∗∗∗ 0.063∗∗∗ 0.039∗∗∗ 0.051∗∗∗ 0.062∗∗∗ 0.041∗∗∗

(0.000) (0.002) (0.000) (0.000) (0.002) (0.000)Trade Openness 0.012∗∗∗ 0.017∗∗∗ 0.005∗∗ 0.012∗∗∗ 0.017∗∗∗ 0.005∗∗

(0.000) (0.000) (0.012) (0.000) (0.001) (0.014)Log (Phone) 0.468∗∗∗ 0.659∗∗∗ 0.382∗∗ 0.471∗∗∗ 0.651∗∗∗ 0.391∗∗

(0.000) (0.006) (0.012) (0.000) (0.007) (0.014)North Africa/ −0.945∗∗∗ −0.574 −1.308∗∗∗ −0.900∗∗∗ −0.536 −1.289∗∗∗Middle East (0.000) 0.178 (0.001) (0.001) 0.225 (0.000)Europe/Central

Asia−0.768∗∗∗ −1.302∗ −0.421 −0.797∗∗∗ −1.290∗ −0.458

(0.001) (0.090) 0.193 (0.001) (0.097) 0.155South Asia −1.976∗∗∗ −2.467∗∗∗ −1.751∗∗∗ −2.028∗∗∗ −2.552∗∗∗ −1.794∗∗∗

(0.000) (0.000) (0.000) (0.001) (0.000) (0.000)Democracy 0.391∗ 0.332 0.453∗ 0.367∗ 0.283 0.377

(0.097) 0.340 (0.095) (0.080) (0.406) (0.123)Mixed 0.406∗∗ 0.774∗∗ 0.305 0.493∗∗∗ 0.775∗∗∗ 0.320

(0.032) (0.014) 0.218 (0.000) (0.034) (0.150)Observations 369 65;65 106;106 369 65;65 106;106R Squared 0.726 0.62;0.75 0.69;0.75 0.727 0.60;0.75 0.69;0.75Reset test (0.213) (0.236)Breusch-Pagan test (0.008) (0.000) (0.007) (0.000)

Notes: Time dummies (in OLS) and constant terms are not reported.Robust standard errors are used in all cases of OLS regression.P-values are reported in parentheses. ∗significant at the 10% level.∗∗significant at the 5% level, ∗∗∗significant at the 1% level.

It is also noteworthy that the mixed category of political regimes, i.e. thosedefined as neither a democracy nor an autocracy, consistently appears with asignificantly positive estimate in the 1983–1992 period regardless of the thresholdused. This may seem to be puzzling at first look, but it is worth reminding ourselvesthat when we use the Polity IV data to classify a regime, the countries in themixed category do not necessarily involve regime changes. Although no obviousexplanation comes into mind, an inspection of the data reveals that this positiveeffect is largely due to the three large FDI recipients, namely, Mexico (with aPolity2 score of −3 in 1983 and 0 in 1988), Malaysia (with a Polity2 score of 4 inboth 1983 and 1988), and Thailand (a Polity score of 2 in 1983 and 3 in 1988),falling into the small group of mixed regimes in the period.

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Table 6. Regime type and FDI/GDP (Dependent variable: log (FDI/GDP), five-year average)

OLS Panel SUR

1983–2002 1983–1992 1993–2002 1983–1992 1993–2002

Log (per capita GDP) −0.182∗∗ −0.214∗ −0.178∗ −0.218∗∗ −0.125(0.012) (0.061) (0.064) (0.029) (0.277)

Growth 0.021∗∗∗ 0.031∗∗∗ 0.016∗∗ 0.020∗∗∗ 0.014∗∗∗(0.000) (0.000) (0.022) (0.002) (0.003)

Trade openness 0.007∗∗∗ 0.008∗∗∗ 0.007∗∗∗ 0.007∗∗∗ 0.004∗∗∗(0.000) (0.000) (0.000) (0.000) (0.008)

Log (Phone) 0.153∗∗∗ 0.141 0.181∗∗∗ 0.223∗∗∗ 0.154∗∗(0.005) (0.146) (0.007) (0.001) (0.033)

North Africa/ −0.400∗∗∗ −0.197 −0.604∗∗∗ −0.333∗∗ −0.624∗∗∗Middle/East (0.000) (0.193) (0.000) (0.013) (0.000)Europe/Central Asia −0.157 −0.155 −0.223∗ −0.361 −0.116

(0.135) (0.584) (0.053) (0.164) 0.430South Asia −0.416∗∗∗ −0.256∗∗∗ −0.574∗∗∗ −0.155 −0.730∗∗∗

(0.000) (0.002) (0.000) (0.346) (0.004)Democracy 0.121 0.205 0.070 0.079 0.078

(0.112) (0.142) (0.484) (0.405) (0.429)Observations 419 178 241 84;84 118;118R Squared 0.459 0.444 0.329 0.42;0.61 0.21;0.41Reset test (0.522) (0.340) (0.908)Breusch-Pagan test (0.000) (0.000)


Regime Type and FDI/GDP

The previous section shows that regime type is not significantly associated withhigh levels of FDI inflows to the LDCs. Does FDI, measured as a ratio to GDP,make a difference? Table 6 gives a negative answer. Here, the total GDP is droppedas a regressor, since FDI is measured as a share of GDP.7 Both the OLS panelregression and SUR estimation deliver consistent results: the democracy dummycoefficients are positive but insignificant, suggesting that regime type is not sig-nificantly related to FDI as a share of GDP. This result is also in line with thefinding of an insignificant impact of freedom on FDI/GNP by Alesina & Dollar(2000).

Table 7 provides the estimation results using the categorical measure of politicalregime based on Polity IV data. Regardless of the thresholds used, similar resultsare obtained, that is, the effect of democracy on FDI/GDP is not significantlydifferent from zero. In short, there is no evidence that regime type is correlatedwith FDI/GDP.

7When it is included in the regressions, the total GDP is insignificant and the democracy estimatesare virtually not affected.

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Table 7. Regime type and FDI/GDP, alternative measure of regime (Dependent variable: log(FDI/GDP), five-year average)


OLS SUR SUR OLS SUR SUR

1983–2002 1983–1992 1993–2002 1983–2002 1983–1992 1993–2002

Log (per capitaGDP)

−0.047 −0.152 −0.035 −0.050 −0.152 −0.032

(0.623) (0.116) (0.780) (0.607) (0.116) (0.796)Growth 0.019∗∗∗ 0.020∗∗∗ 0.014∗∗ 0.020∗∗∗ 0.020∗∗∗ 0.014∗∗

(0.000) (0.000) (0.014) (0.000) (0.002) (0.014)Trade openness 0.006∗∗∗ 0.006∗∗∗ 0.004∗∗∗ 0.006∗∗∗ 0.006∗∗∗ 0.004∗∗∗

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)Log (Phone) 0.089 0.168∗∗ 0.118 0.089 0.168∗∗ 0.108

(0.169) (0.012) (0.186) (0.160) (0.012) (0.225)North Africa/ −0.520∗∗∗ −0.284∗∗ −0.816∗∗∗ −0.506∗∗∗ −0.284∗∗ −0.794∗∗∗Middle East (0.002) (0.028) (0.000) (0.004) (0.028) (0.000)Europe/Central

Asia−0.062 −0.289 −0.098 −0.067 −0.289 −0.085

(0.599) (0.230) (0.578) (0.567) (0.230) (0.635)South Asia −0.405∗∗∗ −0.240 −0.597∗∗ −0.421∗∗∗ −0.240 −0.603∗∗

(0.000) (0.126) (0.022) (0.001) (0.124) (0.02)Democracy 0.081 0.064 −0.016 0.085 0.064 0.012

(0.490) (0.519) (0.913) (0.441) (0.519) (0.930)Mixed 0.089 0.151 0.072 0.127 0.151 0.072

(0.317) (0.124) (0.585) (0.225) (0.124) (0.588)Observations 388 78;78 110;110 388 78;78 110;110R Squared 0.397 0.28;0.49 0.15;0.35 0.398 0.28;0.49 0.15;0.35Reset test (0.340) (0.353)Breusch-Pagan test (0.007) (0.000) (0.007) (0.000)


Regime Type and per capita FDI

Some authors (e.g. Harms & Ursprung, 2002) have used per capita FDI in assess-ing the relationship between political regime and FDI flows, and concluded thatdemocracy attracts higher levels of FDI. To see whether this is the case, Table 8 re-estimates the baseline specification using per capita FDI, but with the total GDPdropped (its inclusion does not affect the results). The OLS regression showsthat the democracy coefficient has a positive sign and is statistically significant atthe 10% level, although this seems to be true only in the 1983–1992 period. TheSUR regression results in Column 4 and 5, however, do not support the view thatdemocracy leads to high per capita FDI, regardless of the periods involved. Sincethe SUR systems take into account the residual correlation (Breusch–Pagan testrejects the null of residual independence) and thus yield a better result, it seems

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Table 8. Regime type and per capita FDI (Dependent variable: log (per capita FDI), five-year average)

OLS Panel SUR

1983–2002 1983–1992 1993–2002 1983–1992 1993–2002

Log (per capita GDP) 0.518∗∗∗ 0.303 0.679∗∗∗ 0.235 0.717∗∗∗(0.000) (0.184) (0.000) (0.316) (0.000)

Growth 0.041∗∗∗ 0.056∗∗∗ 0.029∗∗∗ 0.038∗∗∗ 0.031∗∗∗(0.000) (0.000) (0.003) (0.002) (0.000)

Trade openness 0.011∗∗∗ 0.014∗∗∗ 0.007∗∗∗ 0.014∗∗∗ 0.004∗∗∗(0.000) (0.000) (0.000) (0.000) (0.008)

Log (Phone) 0.428∗∗∗ 0.389∗∗ 0.434∗∗∗ 0.499∗∗∗ 0.405∗∗∗(0.000) (0.014) (0.000) (0.005) (0.000)

North Africa/ −0.954∗∗∗ −0.579 −1.241∗∗∗ −0.675∗∗ −1.273∗∗∗Middle East (0.000) (0.100) (0.000) (0.045) (0.000)Europe/Central Asia −0.641∗∗∗ −0.735 −0.703∗∗∗ −0.321 −0.566∗∗

(0.000) (0.247) (0.000) (0.610) (0.015)South Asia −0.854∗∗∗ −0.556∗∗∗ −1.188∗∗∗ −0.449 −1.410∗∗∗

(0.000) (0.001) (0.000) (0.264) (0.000)Democracy 0.219∗ 0.402∗ 0.163 0.195 0.178

(0.065) (0.089) (0.251) (0.374) (0.240)Observations 410 170 240 78;78 117;117R Squared 0.687 0.61 0.694 0.50;0.70 0.63;0.72Reset test (0.098) (0.391) (0.408)Breusch-Pagan test (0.000) (0.000)


safe to say that regime type is not significantly associated with higher levels ofFDI, at least when we use the PACL measure.

Next, we turn to the Polity IV measure of regime type. Table 9 presents theresults, with the first three columns showing the estimates for threshold (−7, 7)and the last three columns for threshold (−6, 6). In both cases, there is someagreement: democracy is positively and significantly related to higher per capitaFDI in the 1990s. This result seems to be consistent with the finding of Harms& Ursprung (2002, p. 653), who report that, over the 1989–1997 period, ‘indicesof political and civil repression have a significant influence on FDI per capita,and that this influence is negative’. Busse (2004) also finds a positive link betweenenhanced democratic rights and higher FDI per capita in the 1990s. This result,however, is not robust to the measure of regime type. When the threshold (−5, 5)is used (Table 10), the democracy dummy loses its significance (p-value of 0.290)even in the 1990s. Therefore, we do not have much confidence in the proposal thatdemocracy is systematically related to more FDI per capita.

Issue of Endogeneity

It has been shown that, in general, being a democracy is not significantly asso-ciated with more FDI inflows. Still, one may reasonably argue that the results

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Table 9. Regime type and FDI per capita: alternative measure of regime (Dependent variable: log(per capita FDI), five-year average)


OLS Panel SUR SUR OLS Panel SUR SUR

1983–2002 1983–1992 1993–2002 1983–2002 1983–1992 1993–2002

Log (per capitaGDP)

0.602∗∗∗ 0.312 0.766∗∗∗ 0.591∗∗∗ 0.309 0.741∗∗∗

(0.000) (0.245) (0.000) (0.000) (0.246) (0.000)Growth 0.041∗∗∗ 0.037∗∗∗ 0.033∗∗∗ 0.043∗∗∗ 0.037∗∗∗ 0.035∗∗∗

(0.000) (0.002) (0.000) (0.000) (0.002) (0.000)Trade openness 0.009∗∗∗ 0.013∗∗∗ 0.003∗∗ 0.009∗∗∗ 0.013∗∗∗ 0.003∗∗

(0.000) (0.000) (0.019) (0.000) (0.001) (0.014)Log (Phone) 0.338∗∗∗ 0.392∗∗ 0.328∗∗∗ 0.348∗∗∗ 0.384∗∗ 0.342∗∗

(0.000) (0.035) (0.009) (0.000) (0.037) (0.006)North Africa/ −0.839∗∗∗ −0.548 −1.141∗∗∗ −0.816∗∗∗ −0.497 −1.103∗∗∗Middle East (0.000) (0.105) (0.001) (0.001) (0.147) (0.000)Europe/Central

Asia−0.439∗∗ −0.246 −0.353 −0.463∗∗ −0.206 −0.388

(0.019) (0.694) (0.178) (0.014) (0.740) (0.137)South Asia −0.889∗∗∗ −0.673∗ −1.367∗∗∗ −0.940∗∗∗ −0.784∗ −1.400∗∗∗

(0.000) (0.097) (0.000) (0.001) (0.057) (0.000)Democracy 0.319∗ 0.327 0.386∗ 0.316∗∗ 0.331 0.373∗∗

(0.066) (0.205) (0.079) (0.042) (0.174) (0.050)Mixed 0.177 0.445∗∗ 0.235 0.329∗∗ 0.576∗∗ 0.316∗

(0.214) (0.042) (0.239) (0.024) (0.014) (0.073)Observations 379 72;72 108;108 379 72;72 108;108R Squared 0.661 0.44;0.64 0.59;0.70 0.664 0.42;0.66 0.60;0.71Reset test (0.312) (0.206)Breusch-Pagan test (0.000) (0.000) (0.000) (0.000)


could be biased because a number of the explanatory variables are endogenous.This applies in particular to growth rates and trade openness. Using the initialvalues of these endogenous variables at the beginning of each five-year periodcan mitigate the problem in the regressions, but it does not solve it. Therefore,this section uses the generalized method of moments (GMM) dynamic paneldata technique proposed by Arellano & Bond (1991) to deal effectively withthis issue. This method also allows us to control for unobserved country-specificeffects.

The Arellano–Bond estimator includes the lagged dependent variable as aregressor. First differencing each variable eliminates the country-specific effectsand the differenced equation is then estimated by instrumental variables, whichcome from all possible lagged values of each of the variables. When two lags ofthe dependent variable are included in the model, the first three observations will

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Table 10. Regime type and per capita FDI, using (−5, 5) threshold (Dependentvariable: log (per capita FDI), five-year average)

OLS Panel SUR SUR

1983–2002 1983–1992 1993–2002

Log (per capita GDP) 0.597∗∗∗ 0.314 0.762∗∗∗(0.000) (0.239) (0.000)

Growth 0.043∗∗∗ 0.037∗∗∗ 0.033∗∗∗(0.000) (0.002) (0.000)

Trade openness 0.009∗∗∗ 0.013∗∗∗ 0.003∗∗(0.000) (0.000) (0.017)

Log (Phone) 0.354∗∗∗ 0.364∗∗ 0.346∗∗∗(0.000) (0.048) (0.006)

North Africa/ −0.853∗∗∗ −0.417 −1.202∗∗∗Middle East (0.000) (0.232) (0.001)Europe/Central Asia −0.476∗∗ −0.221 −0.411

(0.019) (0.724) (0.114)South Asia −0.898∗∗∗ −0.688∗ −1.371∗∗∗

(0.000) (0.092) (0.000)Democracy 0.247 0.362 0.185

(0.109) (0.133) (0.290)Mixed 0.306∗∗ 0.697∗∗∗ 0.150

(0.044) (0.005) (0.388)Observations 379 72;72 108;108R Squared 0.661 0.43;0.66 0.60;0.70Reset test (0.181)Breusch-Pagan test (0.000) (0.000)

Notes: Time dummies (in OLS) and constant terms are not reported.Robust standard error is used in OLS regression.P-values are reported in parentheses. ∗significant at the 10% level.∗∗significant at the 5% level, ∗∗∗significant at the 1% level.

be lost to lags and differencing. Since this paper has used the five-year averagesof FDI and each country thus has at most four observations in the 1983–2002period, the GMM procedure would result in heavy loss of observations. This isparticularly a problem for countries in Eastern Europe and Central Asia, as thenumber of annual observations for these countries is rather limited. To keep asmany countries as possible, this section therefore employs three-year averagesrather than five-year averages, yielding up to seven observations for each country(the last observation comes from the two-year average in 2001 and 2002).

With this set-up, we can answer the question of whether being a democracyattracts more FDI from another perspective, i.e. whether switching to democracycontributes to FDI growth. To take into consideration the regime changes withina period, this section defines a political regime as democracy if it is a democracyin at least two out of three years within each three-year period, and autocracyotherwise (the value of regime type in 2001 is used for the 2001–2002 period). Thefirst-differenced democracy variable may take the value of 1, 0, and −1, whichcan be interpreted as becoming a democracy, no regime change, and switching to

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Table 11. Regime type and FDI inflows: results using Arellano–Bond GMM estimator

Dependent variable (three-year average, 1983–2002)

log(FDI) log(FDI/GDP) log(per capita FDI)

Democracy 0.009 −0.134 −0.189(0.960) (0.201) (0.250)

Observations 307 387 364Sargan test (0.374) (0.452) (0.441)Arellano-Bond test (1) (0.000) (0.000) (0.000)Arellano-Bond test (2) (0.737) (0.879) (0.276)

Notes: Only the estimated democracy coefficients are presented.Control variables are the same as those used in Table 2, 6 and 8, respectively, but with country-specificeffects rather than regional effects. Period time dummies are included in all regressions.two lags of dependent variable are included in all regressions.Robust standard errors are used for coefficient inference, post-estimation specification tests are doneusing two step estimator. The null of Sargan test is that over-identifying restrictions are valid,The null of Arellano–Bond test (1) and (2) is that there is no first-order and second order autocorrela-tion, respectively, in the differenced residuals, rejection of the null of test (1) does not pose a problem.P-values are reported in parentheses.

autocracy respectively. The democracy dummy variable is assumed to be exoge-nous. Regarding the control variables, both growth rate and trade openness enterthe regressions using three-year averages and are treated as endogenous variables,while the rest take the values at the beginning of each sub-period and are treatedas predetermined. Levels of the endogenous variables lagged two or more peri-ods and of the predetermined variables lagged one or more periods are used asinstruments. Period dummies are included in all regressions.

Table 11 presents the estimation results. As can be seen, none of the democ-racy variables is significant regardless of the FDI measure used. These results areconsistent with what we have seen in the previous sections. Hence, it appears thatswitching to democracy (or autocracy) does not make much difference in termsof attracting FDI inflows. 8

Conclusion

This paper empirically investigates the relationship between political regimesand FDI inflows to the developing countries over the 1983–2002 period. Usingtwo categorical measures of regime type and three different measures of FDI, thisstudy finds no evidence of a systematic relationship between democracy and FDIinflows. This result suggests that being a democracy does not help attract higherlevels of FDI.

8Using regime classification based on the Polity IV polity2 variable gives similar results. Theseresults are available upon request.

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Acknowledgements

I wish to thank Dakshina G. De Silva, Bradley T. Ewing, Yewfoong Lam,Thomas Steinmeier and the two anonymous referees for helpful comments andsuggestions.

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Appendix A. Countries covered in the sample

Sub-Saharan Africa Somalia Kazakhstan SingaporeAngola South Africa Kyrgyz Republic ThailandBenin Sudan Latvia TongaBotswana Swaziland Lithuania VietnamBurkina Faso Tanzania Macedonia, FYRBurundi Togo MoldovaCameroon Uganda Poland Latin AmericaCape Verde Zambia Romania ArgentinaCentral African Rep. Zimbabwe Russian Federation BelizeChad Serbia/Montenegro BoliviaComoros North Africa/Middle East Slovak Republic BrazilCongo, Dem. Rep. Algeria Slovenia ChileCongo, Rep. Djibouti Tajikistan ColombiaCote d’Ivoire Egypt, Arab Rep. Turkmenistan Costa Rica

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Equatorial Guinea Iran, Islamic Rep. Ukraine DominicaEritrea Israel Uzbekistan Dominican Rep.Ethiopia Jordan EcuadorGabon Kuwait South Asia El SalvadorGambia, The Lebanon Bangladesh GrenadaGhana Morocco Bhutan GuatemalaGuinea Oman India GuyanaGuinea-Bissau Syrian Arab Republic Maldives HaitiKenya Tunisia Nepal HondurasLesotho Pakistan JamaicaLiberia Europe/Central Asia Sri Lanka MexicoMadagascar Albania NicaraguaMalawi Armenia East Asia PanamaMali Azerbaijan Cambodia ParaguayMauritania Belarus China PeruMauritius Bosnia and Herzegovina Fiji St. Kitts and NevisMozambique Bulgaria Indonesia St. LuciaNiger Croatia Lao PDR St. Vincent/GrenadinesNigeria Cyprus Malaysia Trinidad and TobagoRwanda Czech Republic Mongolia UruguaySenegal Estonia Myanmar Venezuela, RBSeychelles Georgia Papua New GuineaSierra Leone Hungary Philippines

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Documents

Autocracy, Democracy, and FDI Inflows to the Developing Countries