Institute for Development Policy and Management (IDPM)

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1 Institute for Development Policy and Management (IDPM) Development Economics and Public Policy Working Paper Series WP No. 33/212 Published by: Development Economics and Public Policy Cluster, Institute of Development Policy and Management, School of Environment and Development, University of Manchester, Manchester M13 9PL, UK; 1

2 Do We See Convergence in Institutions? A Cross- Country Analysis Antonio Savoia 1 and Kunal Sen Institute for Development Policy and Management, University of Manchester Arthur Lewis Building, Oxford Road, Manchester, M13 9PL, United Kingdom Abstract Are contemporary differences in institutional quality between countries transitory or permanent? The literature is ambivalent on whether we should expect convergence in the quality of institutions across countries over time. Since institutions are seen as a fundamental cause of economic growth, we present some stylised facts and, using cross-section and panel data methods, test for convergence in the quality of institutions in a large sample of countries since the 198s. The evidence suggests that legal, bureaucratic and administrative institutional quality tended to (slowly) rise in countries with initially poor governance, while they have remained stable in countries with initially good institutions, from the mid 198s to the mid 199s. However, we also find that the convergence process has considerably weakened since the mid 199s. Keywords: Convergence, Institutions, Institutional Change, Growth, Economic Development JEL Classification Code: O1, P1, P5 1 Corresponding author. [email protected]; phone: +44 ()

3 1. Introduction One of the most important findings in the literature on the determinants of economic growth is that differences in the quality of institutions (defined as the quality of rules, regulations, laws and policies that affect economic incentives to invest in technology, physical capital and human capital) explain in large part differences in per capita income across countries (Hall and Jones 1999; Acemoglu, Johnson and Robinson 21). Rich countries, especially those located in the North America, Western Europe, Australia and New Zealand, have better quality institutions than countries in the developing world. As Acemoglu (29) argues, there is convincing empirical support for the hypothesis that differences in economic institutions, more than luck, geography or culture, cause differences in incomes per capita (p.123). If institutional quality is a crucial determinant of economic growth, do we observe convergence in institutional quality as low income countries with poor quality institutions adopt the best practice institutions that are prevalent in the richer countries? In this paper, we examine how institutional quality evolves over time, and whether we see convergence in institutional quality, across countries. Since the literature on the empirics of economic growth is unclear on the precise type of institution that matters for economic growth (Bardhan 25), we use a variety of institutional quality measures, such as the administrative and legal capacity of the state (Besley and Persson 211), the rule of law (Haggard and Tiede 212), the risk of expropriation and the security of property rights (Acemoglu, Johnson and Robinson 21). We use different data sets and periods of analysis, depending on the institutional variables that we examine, with our sample of countries ranging from 9 to 179, and our longest period of analysis being

4 We find that institutional quality as measured by legal, bureaucratic and administrative quality indicators by the Fraser Institute (Gwartney and Lawson 27), the World Bank (211) and the International Country Risk Guide (Teorell et al. 28; ICRG 1997) tended to (slowly) rise in countries with initially poor governance, while they have remained stable in countries with initially good institutions, from the mid 198s to the mid 199s. However, we find that the convergence process was less evident since the mid 199s. While the end of the Cold War in the early 199s may explain why there was convergence in institutional quality in the period till the mid 199s, our paper finds that the positive effect of the end of the Cold War on the catch-up of the institutions of transition and developing economies to the high quality institutions of advanced market economies has weakened in the new millennium. The paper proceeds as follows. In Section 2, we briefly discuss the theoretical and empirical literature on institutions and review what we may expect from the literature on whether institutional quality may converge across countries. Section 3 illustrates the data. Section 4 discusses the methodology and the results. Section 5 concludes. 2. Why we may expect convergence in institutional quality (and why we may not)? Should we expect convergence in institutional quality across countries? Both the theoretical and empirical literature remain ambivalent about this possibility. For example, La Porta et al (28: 327) speculate that convergence in institutional quality will occur as a result of increasing globalisation, as it leads to faster exchange of ideas and to higher competition for FDI. This, in turn, will respectively encourage the transfer of legal knowledge and the adoption of good regulations. But the process of institutional reform, and eventual convergence, may be rather slow, as the appropriate choice of institutions depends 4

5 on a society s initial conditions (Djankov et al. 23). Historically, with the end of the Cold War in the early 199s, both ex command economies and non-socialist developing economies had undergone major institutional changes, adopting similar production and exchange mechanisms based on privatisation and deregulation in the late 198s and early 199s. The adoption of market institutions of the West in developing and transition economies was accelerated by the spread of the post-washington Consensus among donor agencies and Southern governments in the 199s, which aimed at the creation of institutions that helped markets (e.g. legal framework and institutions, property rights, competition policy and contract enforcement) (Stiglitz 1998). Institutional mono-cropping was the prevalent norm as international organizations, local policy makers and private consultants combine(d) to enforce the presumption that the most advanced countries have already discovered the one best institutional blueprint for development and that its applicability transcends national cultures and circumstances (Evans 24: 33). The transplanting of what were considered as best practice institutions to developing and transition economies occurred in the 199s in a decade which was widely seen as the decade of institutional reform (Mkandawire 212). However, institutional mono-cropping did not seem to deliver the results in terms of expected economic performance in countries which adopted Westernstyle institutions (Chang 27), in part due to the lack of fit with the prevailing social and cultural context (Rodrik 28; Roland 24) and in part due to the fact that governments in developing countries did not have the capabilities to enforce the successful functioning of these institutions (Khan 212). This may have led to a weakening of the incentives of Southern policy-makers to adopt Western-style institutions over time (Mkandawire 212). From a theoretical standpoint, new institutional economics argues that poor quality institutions will not persist over time, as economic agents realise the growth enhancing effects of better quality institutions (Williamson 1996) and seek to replace inefficient 5

6 institutions with more efficient institutions. However, such a positive view of institutional change has been challenged by other views looking at the role of social conflict and the elites. A conflict over the distribution of resources creates insurmountable commitment problems for institutional change. For the rich (poor) cannot commit to compensate the poor (rich) after old rules have been replaced with new ones (Acemoglu, 23; Bardhan, 25). As a result, bad institutions can persist. Taking this view further, Acemoglu and Robinson (26, 28) argue that institutional reforms may be hindered by elites who benefit from existing economic institutions. Political elites who hold power will always have an incentive to maintain the political institutions that give them political power, and the economic institutions that distribute resources to them. Therefore, there would be a persistence of poor quality economic and political institutions in such societies, since the elites who benefit from these institutions would not have any incentives to change them (Acemoglu and Robinson 212). Similarly, inspired by the facts of the Russian transition, Sonin (23) argued that wealthy elites may prefer to establish corrupt relationships with state authorities in order to manipulate the legal system in their favor, rather than supporting public protection of property rights, so perpetuating a system with poor property rights institutions. The above discussion suggests that ultimately, whether economies with poor quality institutions catch up with economies with high quality institutions, and how fast, are a matter of empirical debate as neither the theoretical nor the previous empirical literature provides any clear and unambiguous answer on what we may expect. In this paper, we investigate whether there has been a process of catch-up in countries with poor quality institutions through simple convergence tests. Before we proceed to the tests for convergence, we describe the data that we will use and provide some descriptive statistics on the evolution of institutional quality across countries. 6

7 3. Variables and Descriptive Statistics This section illustrates the measures of institutional quality, examining the trends of legal, bureaucratic and administrative institutional quality measures. We use cross-country data with the longest temporal (and a substantial geographical) coverage provided by International Country Risk Guide (ICRG 1997), the World Bank (211), Fraser Institute (Gwartney and Lawson 27) and Teorell et al (28). The appendix provides details on each database and on the countries observed. The IRIS database (ICRG, 1997), constructed by Knack and Keefer (1995) from the International Country Risk Guide, covers the period in table 1. The data comes from subjective assessments of foreign investors and business experts. It includes the government repudiation of contracts, the expropriation risk, rule of law, corruption in government, and bureaucratic quality indices. The first three are indicators of legal capacity of the state; the last two capture the level of bureaucratic and administrative capacity. Table 1 shows their trends, comparing economies at different stages of development. A first stylised fact is that developing and transition economies institutional quality fared well below the advanced countries average along all five dimensions until 199. But, post the end of the Cold War in the early 199s, such countries experience sizable institutional quality improvements, mainly along three dimensions. While bureaucratic and administrative capacity improves but still retains low ratings (i.e., bureaucratic quality and corruption in government), the legal capacity components (expropriation risk, government repudiation of contracts and rule of law) tend to move closer to the averages of developed countries. This suggests that the end of the Cold War has been a positive shock for 7

8 institutional quality. 2 A second noteworthy fact is the decrease in the cross-sectional dispersion over time of all five measures (expressed by the Coefficient of Variation). This has been rather sharp, regardless of the countries stage of development, for expropriation risk and government repudiation of contracts. Bureaucratic quality, corruption in government and the rule of law have also seen a decrease in cross-sectional dispersion, but not as pronounced. The cross-sectional dispersion in bureaucratic quality and corruption in government has, instead, increased in transition economies. 2 The regional trends across the developing world reflect this evidence. Bureaucracies improved less and retain low scores across the Middle East & North Africa region, sub-saharan Africa, Latin America and Asia. On the contrary, expropriation risk, government repudiation of contracts and rule of law improve substantially in all regions (with higher increases in Middle East & North Africa). 8

9 Table 1: Institutional quality the world around: ICRG data, Year Panel (a): Bureaucratic quality Whole sample Mean CV N Advanced economies Mean CV N Developing Economies Mean CV N Transition Economies Mean CV N Panel (b): Rule of Law Whole sample Mean CV N Advanced Economies Mean CV N Developing Economies Mean CV N Transition Economies Mean CV N Panel (c): Corruption in Government Whole sample Mean CV N Advanced Economies Mean CV N Developing Economies Mean CV N Transition Economies Mean CV N Panel (d): Expropriation Risk Whole sample Mean CV N Advanced Economies Mean CV N Developing Economies Mean CV N Transition Economies Mean CV N Panel (e): Government Repudiation of Contracts Whole sample Mean CV N Advanced Economies Mean CV N Developing Economies Mean CV N Transition Economies Mean CV N Notes: data is from ICRG (1997). Countries classification follows the IMF system, based on per capita income level, export diversification and degree of integration into the global financial system ( accessed on 25/8/211). 9

10 Institutional quality is a slow-changing phenomenon and it should be analysed over a longer period. The IRIS database only stretches to 1997, but a longer view of the historical evolution of institutional quality is still possible if we resort to other databases. Given its most extensive country coverage, influential articles on governance and development (e.g. Rodrik et al., 24) utilised data from the World Governance Indicators (WGIs) by the World Bank (211). 3 Four (out of six) indicators assess dimensions of institutional quality: rule of law, regulatory quality and government effectiveness, as well as control of corruption. The first three indicators express the degree of legal, infrastructural and administrative institutional quality, respectively. The remaining one is a proxy for bureaucratic capacity. These are all subjective measures that try to improve on country coverage by aggregating the ratings from over thirty organisations. Higher scores indicate better ratings. Table 2 compares developing, advanced and transition economies over Bearing in mind that the inference of time trends may reflect, as Kauffman et al. (29) warn, changes in the number of underlying data sources used, one stylised fact is that institutional quality from the mid 199s to the late 2s has been stable in both rich and poor countries. Hence, the gap between advanced economies and the rest is unchanged. A second stylised fact is that, along all four dimensions, advanced economies remain a more homogenous group than developing and transition economies, which show much greater variability in institutional quality in The data are rescaled to lie between and 5 (instead of being centred on zero, as in the original dataset), as the Coefficient of Variation would otherwise be very volatile. 1

11 Table 2: Institutional quality the world around: WGIs, Year Panel (a): Government Effectiveness Whole sample Mean CV N Advanced economies Mean CV N Developing economies Mean CV N Transition economies Mean CV N Panel (b): Regulatory Quality Whole sample Mean CV N Advanced economies Mean CV N Developing economies Mean CV N Transition economies Mean CV N Panel (c): Control of Corruption Whole sample Mean CV N Advanced economies Mean CV N Developing economies Mean CV N Transition economies Mean CV N Panel (d): Rule of Law Whole sample Mean CV N Advanced economies Mean CV N Developing economies Mean CV N Transition economies Mean CV N Notes: World Bank (21) data. The variables are rescaled to lie between and 5. Countries classification follows the IMF system, considering per capita income level, export diversification and degree of integration into the global financial system ( retrieved on 25 th Aug 211). Two further databases, measuring similar dimensions of institutional quality, allow to observe the longest period: the Quality of Government index assembled by Teorell et al (28) and the Quality of Legal Structure and Security of Property Rights index (Gwartney and Lawson 27). The Quality of Government index is calculated as the average of rule of law, corruption in government, and bureaucratic quality indices from various editions of the 11

12 International Country Risk Guide (the other two components seen above were discontinued after 1997). It spans from 1984 to 28 and is rescaled to lie between and 1. The Quality of the Legal Structure and Security of Property Rights, which is a component of the Fraser Institute index of Economic Freedom, is a continuous variable ranging between 1 and 1, with a higher score corresponding to higher quality of institutions. This is the only available indicator over a long time span, also for a number of developing economies. It has, in fact, been recorded every five years from 197 until 2 (and every year from 21 on), but between 197 and 1975 only fifty countries are observed. Unfortunately, it samples fewer countries than the ICRG database. The index has been assembled over the years from different sources essentially, but not exclusively, from: the ICRG, the Business Environment Risk Intelligence and the Global Competitiveness Report and has undergone some changes in definition, although the underlying concept remains unchanged (see, for details, Gwartney and Lawson 27). Table 3 takes the longest possible view. Since the 198s, a remarkable fact is that both measures signal that the end of the Cold War was accompanied by sharp improvements in institutional quality. Both developing and advanced economies have, at the end of the period, experienced improvements in the Quality of Legal Structure and Security of Property Rights (which were relatively larger in developing economies). The Quality of Government index, instead, remained essentially stable in both advanced and developing countries over the period. The transition economies experienced deterioration in institutional quality, according to both measures. Finally, it is noteworthy that the cross sectional dispersion over the whole sample, from the beginning to the end period, decreases in both measures. However, the decrease is monotonic in both measures until 1995, but subsequently the coefficient of variation picks up again or becomes stable, so suggesting that the likely catching up effect in institutional quality has stopped or decelerated. 12

13 Table 3: Institutional quality the world around: Panel (a): Quality of legal structure and security of property rights index Year Whole sample Mean CV N Advanced economies Mean CV N Developing economies Mean CV N Transition economies Mean CV N Panel (b): Quality of Government index Year Whole sample Mean CV N Advanced economies Mean CV N Developing economies Mean CV N Transition economies Mean CV N Notes: data is from Qwartney and Lawson (27) and Teorell et al (28). Countries classification follows the IMF system, based on per capita income level, export diversification and degree of integration into the global financial system ( accessed on 25/8/211). This can be seen also in Figure 1 below, which provides further details by disaggregating the developing countries group into macro regions. Quality of Government shows a spike for all groups of countries in the mid 199s, where all regions of the developing world seem to move closer to the advanced economies. But the subsequent worsening slows this process, although some convergence seems to have occurred. The Quality of Legal Structure and Security of Property Rights presents a similar evolution across regions. Note also that in both cases the transition economies have experienced a decrease in institutional quality after the end of the Cold War. The group of countries that has improved institutional quality most compared to its initial level is the MENA region (followed by Latin America), in terms of the Quality of Legal Structure and Security of Property Rights, and Asia (followed by Latin America), in terms of the Quality of Government. 13

14 Legal structure and property rights Advanced econ. Latin America sub-saharan Africa Asia MENA Transition econ Time Quality of government Advanced econ. Latin America sub-saharan Africa Asia MENA Transition econ Time Figure 1 Institutional quality time paths by level of development Finally, we look at how successful individual countries have at improving institutions. Table 4 gives the list of most and least successful countries at reforming institutions over the period They are arranged according to (average) annual growth rates of the Quality of Government and Quality of Legal Structure and Security of Property Rights indices. The table reports the countries in the top and bottom quartiles, together with their initial levels in The most significant institutional changes since 1985 have occurred mainly across the developing world, spreading across all regions. Nine of the most successful reformers, according to panel (a), are Latin American countries; six are sub-saharan Africa economies; five are located in the MENA region and three are Asian developing economies. Looking at the worst reformers, ten are sub-saharan Africa economies and seven are Latin American, followed by four from Asia and five amongst the advanced economies. Regarding panel (b), eleven of the best reformers are Latin American countries; eight are sub-saharan Africa economies; five are Asian and four are in the MENA region. Sixteen of the worst reformers, instead, are in sub-saharan Africa; five are Latin American and four Asian states. 14

15 Table 4: Institutional reforms, Panel (a): Quality of legal structure and security of property rights index Best reformers Worst reformers Country level Country level code growth rate code growth rate 1. IRN CAF PER VEN GTM CIV GUY TGO BOL CMR SLV TCD MLT BGR GHA MDG TUN SLE PHL ECU JOR BDI CYP MMR NIC PNG UGA ITA GNB HTI NGA BEL KOR KEN JAM USA LKA ISR MAR DOM ZMB NER ROM PRY SYR BRA PAN TWN BGD CHN CHL MEX MLI CZE Panel (b): Quality of Government index Best reformers Worst reformers Country level Country level code growth rate code growth rate 1. BGD SOM PHL CIV UGA VEN GUY NER BOL KEN IDN PRK HTI ZWE SLV SLE PAN ZAF ROM PNG GTM BRA GHA BGR LBR MOZ MLI DOM SYR THA HND BFA VNM CRI QAT GAB TZA MDG CYP ALB ZMB BWA PER MYS BHS ITA MMR CUB PRY BEL ETH IRQ LBN CMR ZAR TGO CHL SEN IRN COG Notes: data is from Qwartney and Lawson (27) and Teorell et al (28). 4. Convergence tests Since we are interested in whether poorer countries are narrowing their institutional quality gap with richer countries, which is a between-country regularity, cross section data is an appropriate place to look for evidence of convergence. The simplest test for convergence is to regress the observed changes over time on a given measure on the measure s initial 15

16 values across countries. Let G it denote the observed institutional quality measure in country i observed at both date t= and t=t, i.e., at the beginning and at the end of the sample period respectively. A test equation for institutional quality (unconditional) convergence is then: (lng it lng i )/T = α + β G i + ε i with i=1,..., N (1) where the dependent variable is the average annual growth rate in institutional quality, α and β are parameters to be estimated and ε i is a zero mean error term. According to (1), a negative (positive) estimate of the parameter β implies that there is institutional quality convergence (divergence). Rate of change BGD PHL UGA GUY BOL IDN.5 HTI SLV GTM ROM PAN GHA LBR MLI HND PRY MMR ZMB SYR PER TZA VNM QAT BHS CYP ZAR LBN ETH IRN CHL GINJAM JOR KOR SDN LBY LKA TUN MAR KWT ARE NGA MEXOMN GRC POL PAK URY IND EGY TUR PRT ESP ISR IRL MWI RUS DZA NIC TTO AUT AGO ARG CHN CZE DEU AUS BHR BRN CAN DNK FIN COG COL GBR NOR LUX NLD NZL ISL CHE CMR ECU SAU SVK TWN SGP SWE HUN JPNUSA TGO FRA IRQ SEN CUB BEL GABALB BWA ITA BFAMDG MYS CRI DOMMOZ THA BGR SLE PNGBRA ZWE PRK ZAF KEN VEN CIV NER -.5 Rate of change IRN PER GTM BOL GUY SLV MLT GHA TUN PHL JOR GNB NICUGA NGA.2 JAM LKA BGD SYR COG HND MLI PAN COL DZA -.2 ZAR ZWE HTI PAK CYP KOR ROM MAR ZMB CHL MWI ZAF BRB POL HKG CRI OMN BHS GBR KWT IND ARE IRL BHR TTO PRT BWA BEN ALB URY EGY MYS GRC ESP GAB IDN TZA MUS SEN ARG THA MEX TUR BRA CHN HUN CZE PRY NER KEN DOM ISR ITA PNG MMR MDG BDI ECU SLE TCD TGO CMR CIV SGP SWE NZL DEU DNK FIN NOR FRA JPN AUS CAN AUT ISL CHE LUX NLD TWN BEL USA BGR Rate of change KWT IRN ARE.4 MAR JOR SYR GUY EGY GHA GTM SLV UGA.2 NIC BOL JAM PAK HND PAN MWI PHL PERISR BGD TUN NGA IDN LKA CRI SWEFIN DZA ISL NOR ZWE GBR DNK HTI ZAR SEN GAB CHL CAN AUS COL ARG KEN FRAIRL NLD NZL MLI DEU LUX GRC ITA ESP AUT HKG CHE IND KOR PRY TUR URY ZAF MYS SGP BEN TTO ZMB TZA JPN COG NER BRA THA TWN BEL USA DOM PRT MEX TGO BDI ECU CMR TCD MMR -.2 SOM CAF VEN CAF VEN Quality of Gov Legal System and Prop. Rights Legal System and Prop. Rights 198 Rate of change GUY PRY IDN POL GHA MMR ROM GTM BGD UGA HND PAN SDN BOL ETH SLV TZA URY IRN.5 PHL GIN SVK ZAR GMB VNM NGA YUG QAT RUS SYR LBY PRT OMN GRC JAM CZE JOR TUR CHL MEX AGO TWN KOR CYP ESP HUN ISR ITA AUT IRL NOR KEN DEU LBR HTI COG GNB TGO ZMB MWI PER SUR DZA ALB LBN IRQ NIC DOM KWT MOZ ARG BGR EGY ARE CHN ECU PAK SEN VEN TTO TUN LKA CRI CMR MYS ZWE GAB PNG BHS BRA THA CIV IND HKG SGP LUX SWE GBR AUS CAN CHE DNK USA BEL NLD NZL ISL MLI FRA JPN FIN BWA MAR BHR SAU COL MDG CUB PRK BFA ZAF SLE -.5 SOM NER Bureaucratic Quality 1985 Rate of change GUY UGA LBN LBY LKA PHL.1 GTM BGD GHA NGA PER SUR BOL SLV HTI MAR ROM YUG CYP SYR TUN IRN COL IRQ ZWE ZMB MWI PAK PRY RUS JOR IDN IND NIC KWT QAT ISR.5 GRC OMN VNM ARG CHN PRK ETH THA TZA ZAF MMR COG GAB TGO HND JAM PAN SEN DZA MLI ESP KOR IRL DOM EGY ARE BFA TUR GMB BHR SAU POL CHL GBR SGP DEU HUN CZE JPN ITA AGO PRT GNB ZAR SDN CMR MOZ URY GIN BHS ECU KEN VEN TTO CRI MYS HKG CUB SVK FRA SWE NOR AUS CAN CHE DNK USA AUT LUX NLD NZL FIN ISL MEX BEL LBR BWA TWN BGR MDG PNG BRA CIV SOM ALB SLE -.5 NER Rule of Law 1985 Rate of change BOL IRN ARG.1 GUY IRQ LBY SLV NIC GTM SURSYR PER LBN PHL BGD AGO GHAJOR GRC COG ZWE HND PRK MEX EGY JAM PAK DZA POL TUN CHL BFA DOM PAN URY TTO.5 GNB SDN ROM KWT CYP SAU PRT THA LKA UGA NER HTI MMR COL MDG NGA OMN MAR MOZ ZMB ARE KEN MWI VEN TUR ALB TZA CRI IDN GIN BWA HKG KOR BHR BHS BRA ZAF PNG CMR TGO ECU PRY ETH IND ZAR MYS VNM GAB YUG CUB QAT SWE CHN ESP HUN CZE ISR ITA GMB SVK TWN GBR NOR SGP AUS CAN DEU DNK AUT FRA BEL JPN NZL FIN IRL ISL BGR SOM MLI SEN CIV RUS CHE USA LUX NLD SLE LBR Expropriation risk 1985 Rate of change GUY BOL IDN MLI UGA PRY GTM KOR SYR.5 SLV CYP ROM MAR GHA ZMB JAM SUR TTO SLE CMR PAK GRC VNM DOM JOR CHL LBY LKA IRN ECU GIN ESP HUN POL PRT DEU LBR EGY GNB NGA TGO HND PAN QAT GMB OMN COG KWT PNG YUG BHR CUB KEN PER SEN URY VEN THA TUN TZA IND MDG MOZ BGR CZE ITA HKG AUS CRI SWE CAN DNK NLD FIN ISL AUT JPN ISR ZWE NIC AGO LUX NOR CHE ZAF NZL BWA MYS USA IRL TWN BRA MWI SVK BFA DZA GBR MEX ARE SAU COL ETH TUR CIV SGP FRA BEL -.5 MMR SDN ARG CHN RUS ALB GAB PRK LBN IRQ -.1 SOM Corruption in Gvt Rate of change BOL ARG ECU PER QAT IRQ.1 DOM LBN LBY PHL IRN ARE SAU NGA MAR POL BGDTUN SYR GHA JORROM MEX LKA UGANIC SLVEGY PAK CHL OMN GRC KWT GUY BRA MWI PAN CRI CYP ETH TUR IDN SUR VEN DZA BWA BHR JAM THA IND CHN GMB COG ESP HUN CZE AGOMMRCMR GAB CUB VNM NER ISR KOR GTM HND TZA MYS PRK PRY SVK URY ZWE YUG TWN SGP AUS PRT NZL IRL ISL GIN KEN FRA SDN TTO ZAF BHS MOZ SWE NOR DNK USA AUT JPN NLD DEU FIN BEL MDG GNB TGO ZMB SEN BFA HTI HKG CAN ITA GBR LUX CHE CIV BGR COL RUS PNG MLI SLE ALB ZAR SOM -.1 LBR Gvt. Repudiation of Contracts 1985 Rate of change DMA.5 RWA LBR MLT SUR VCT BIH ETH KAZBGR SYC LVA GRD URY KNA LTU TZA HRV IRQ BLR NER ROM GEO TJK ARMPAN JAM QATEST GHA COG AGO ARE BHS CMR MUS LCA SDNGA KHM BRA BWA BTN MDG IRN MWI CYP BFA LKA TUR CRI CUB BHR CHL ECU DOM DZA IND KOR SLB RUS PERSLV MEX TTO SVKSVN ZAR HKG HND MKD MYS UGA SAU CPV AUS DJI AZE VNMAR GUY PHLCHN OMN POL HUN CZE FIN ISL BLZ JOR PRT DNK GIN GAB MLI UZB STP KGZ ALB MDV COL GRC ISR UKR VUT AUT BDI ZMB MNGMOZ KEN BRN CAN SWE BGD GTM KWT JPN NIC MDA SYRTON TUN BOL IDN ESP FRA NZL SWZ ZAF ITA TWN SGP BEL IRLGBR GMB EGY LBN DEU NOR PAK LUX SEN NLD VEN THA NAM CHE GNQ GNB PNG USA LSOARG PRY BEN YEM KIR NPL TKM LBY SLE FJI PRI CAF MMRHTI TGO LAO MRT TCD ERI -.5 CIV COM ZWE PRK SOM Govern. Effectiveness 1996 Rate of change TJK.1 LBY RWA GMB ETH ARM GEO SDN LAOSYC BDI NER BLR AGO MOZ AZECPV ROM BIH UZB NGA MNG SAU MKD MUS AUS ALB BGR CAN IRN DMA BHR BEL CHECHL CMR AUT BFA BRA BHS CZE DEU FIN SLE KGZ GRD HRVISL JPNFRA DNK ESP HTI KAZ HND KEN KNA KWT VCT LCA OMN SVK ZAF KORHUN MLT CYP IRL EST GBR HKG LBN ITA LTU GHA ISR NORNLD LUX MRT NPL PNG POL SWE LSO NAM QAT DOM JORARE COL CRI DZA CHN BWA GRC LVA MDG RUS SEN TWN NZL MYS PAK FJI NIC IND MDA MAR PER MWI GTM PAN PRI SGP SLBSYR USA SUR UKR SLV SVN BRB COG BLZ BEN EGY JAM MEX PRT TCD THA TUR YEM VNM TTO TZA GNQ STP KHM MLI UGA TON BGDGAB GUY MDV IDN LKA TUN URY SWZ PHL CAF CIV VUTDJI ZMB PRY CUB COM KIR GNB ARG ECU GIN BTN TGOBOL VEN ZWE -.1 PRK MMR ERI Regulatory Quality 1996 Rate of change LBR.1 LAO RWA BTN.5 ZAR BRB GNB SDNCMR TGO DZA CUB GAB GEO HRV AGOSLEMOZ MLT COG LBY MWI SUR QAT NGA COL LVA NER GHA EST IRQ HTI AZE ARMBFA BRA BGD BGR BHR CYP IRN ETH KAZ UGA LTU KHM YEMMDG MLI ROM TUN SVK BWA BRN HKG TJK KOR BHS CHLBELCAN AUS CHN CPV CRI CZE GNQKEN MRT VNM ZMB SEN LSO PAN LKA MUS SVN LUX PER SYR TUR URY HUN DEU DNK AUT FIN CHE BLRDOM EGY ESP FRAIRL GBR ISL GIN GTMHND MEX JAM JOR KWT JPN MDA MKD NAM POL PRI TWN PRK OMN NLDNOR NZL PAK IDNALB MYS PRT SGP SWE SLV RUS TZA ZAF USA BIHMARIND SAU AREGRC ISR MMR BDI PNG UKR BEN LBN DJIMNG GUY ITA TKM NIC PHL UZB CIV PRY ARG TTO THA GMB TCD KGZ ECU BOL NPL BLZ FJI SWZ CAF ERI AFG -.5 VEN ZWE -.1 SOM Rule of Law 1996 Rate of change ZAR.1 LBR SLE.5 GEO MKD QAT GAB TZA LVA ARE BGR EST TKM ZMB GTM SAU ETHBOL HRV BHS GHA URY SLV NGA LTU CUB BWA CMR BRN MLT IRQ KEN BLR PAN TJK BHR OMN ARM BRA HKG LAOHND JPN JOR MUS SOM TGO IRN MWI COLROM CHL BEL AUS ISL BFA BIH CRI DNK GNBECU MOZ JAM LUX KOR ESP FRA NZL KHM VNM DZA MEX THATUN POL CHE CAN FIN AZE KAZ AUT GUY ARG CZE DEU IDN IND LKA KWT IRL SGP SWE NLD PAK SUR TUR PER SVK TWN NOR SVN HUN SDN HTI SYR UKR SEN PRY NER MLI MAR CYP GBR ALB GRC ITA MYSNAM PRT USA RUSUGA ZAF AGO UZB LBYKGZ DOM MDA PRI CHN COGBGDPHL MDG ISR VEN LBN NIC EGY GNQ GMB MMR PNG YEM MNG NPL TTO PRK -.5 ZWE CIV GIN Control of Corruption 1996 Figure 2 Initial level of institutional quality vs. subsequent rate of change: various measures Figure 2 presents the scatter plots for all the measures illustrated above. The variables with the longest time coverage, Quality of Government and the Quality of Legal System and Security of Property Rights, both suggest evidence of convergence. Likewise, the five ICRG measures suggest that economies with weaker institutions in the 1985 are expected to catch 16

17 up with the economies having high-quality institutions to start with. However, the convergence process does not seem to be as evident when plotting the WGIs. 4.1 Baseline results Table 5 reports the results of the test on the measures of Quality of Government, for the period , and the Quality of Legal System and Security of Property Rights for The estimates, in panel (a), show that within-country institutional quality has been converging since the 198s, with the coefficients on initial measures both negative and statistically significant at the 1 per cent level. To give an appreciation of the speed of convergence, consider Quality of Legal System and Security of Property Rights in Bangladesh in 1985, scoring 2.46 (out of 1), and South Korea, scoring 4.16 (the former is often cited as an example of poor institutions, the latter is known in the literature on developmental States as an example of effectiveness). According to the estimates in the second column, the expected average annual growth in Quality of Legal System and Security of Property Rights will be.16 percentage points in the former case and.9 in the latter. After 24 years, the two countries are predicted to reach a rating of 3.4 and 5.7, respectively. This is indicative of a significant, albeit slow, process of convergence over the period , where economies with low-quality institutions may remain so for generations. Repeating this exercise for the Quality of Government index leads to similar conclusions. The convergence regressions in panels (b) and (c), however, may suggest that the convergence process has changed over time. Results using the ICRG measures suggest that convergence did occur during the time leading to the end of the Cold War and its immediate aftermath ( ), with convergence parameters always negative and strongly 17

18 significant. 4 But after such period, tests using the WGIs measures hardly show any evidence of convergence (apart from the Control of Corruption index) and initial levels of institutional quality (in this case, taken in 1996) explain little variation in its subsequent growth rate. These contrasting results call for further analysis on the evolution of the convergence process documented so far. 5 Table 5: Convergence in institutional quality regressions Panel (a): Teorell et al. (28), average annual growth, and Fraser Institute measures, and average annual growth Quality of government Quality of Legal system and property rights, Initial value, *** -.4*** (.7) (.1) Initial value, *** (.1) Constant.3***.26***.26*** (.5) (.3) (.4) F-stat *** 49.91*** 46.48*** Adj. R-Sq Obs RMSE Panel (b): ICRG measures, average annual growth Bureaucratic quality Rule of law Corruption in government Quality of Legal system and property rights, Expropriation risk Government repudiation of contracts Initial value, *** -.11*** -.7*** -.11*** -.11*** (.1) (.1) (.1) (.1) (.2) Constant.45***.87***.38***.13***.92*** (.6) (.6) (.9) (.7) (.11) F-stat *** *** *** *** *** Adj. R-Sq Obs RMSE Panel (c): WGIs, average annual growth Government effectiveness Rule of law Control of Corruption Regulatory quality Initial value, *** -.8* (.1) (.3) (.2) (.4) Constant (.1) (.2) (.2) (.2) F-stat *** 3.242* Adj. R-Sq Obs RMSE Notes: the dependent variable is the average annual growth rate of each institutional measure. Symbols *, ** and *** stand for significant at 1, 5 and 1% respectively, two-tailed test. Heteroskedasticity-Robust Standard errors are in parentheses. 4 The speed of convergence can vary though. Consider Bureaucratic Quality in 1985 in Bangladesh, scoring 1.67, and South Korea, scoring According to the estimates, the expected average annual growth in this index will be 3.46 percentage points in the former case and.41 in the latter. After 12 years, the two countries are predicted to reach a bureaucratic quality of 2.36 and 6.99 (out of 1), respectively. This is, again, suggestive of slow convergence. Convergence seems to be faster, instead, for the Expropriation Risk measure. In this case, the expected average annual growth in this index will be 5.89 percentage points in Bangladesh and 2.57 in South Korea. After 12 years, the two countries are predicted to score of 6.83 and 9.16 (out of 1), respectively. 5 The results are insensitive to checks for influential and outlying observations. By excluding from the regression countries with large DFITS statistics (the threshold is DFITS > 2 k / N ), we conclude that influential observations do not significantly affect our estimates. Similarly, we have calculated DFBETA statistics to check whether influential observations affect the magnitude of the convergence coefficient, β. Its estimate shows little sensitivity once we remove from the regressions values that are above the cut-off DFBETAj > 2 N. In sum, this exercise provides evidence in support of the generality of the results. 18 j

19 4.2 Further results: convergence pre- and post-cold War Has the convergence process stopped or slowed down over time? This section tests if the speed of convergence has been constant pre- and post-cold War. We do this by dividing the period under scrutiny into two sub-periods: and Since the Cold War effectively ended in 1991, the sub-periods broadly capture whether the speed of convergence was faster in the period immediately following the end of the Cold War as compared to the subsequent period. 6 Figure 4, which reports the plots of Quality of Government and Quality of Legal System and Security of Property Rights by sub-periods, reveals that, while over the window there seems to be convergence, the negative relationship is weaker after 1995 for both measures..2 BGD.1 HTI GUY UGA PHL LBR Rate of change BOL IDN PRY ROM SLV GHA GTM LBY MLI MMR SYR IRN ZAR NGA LBN TZA VNM QAT HND PAN JOR KOR GRC CYP POL ZMB JAM BHS SDN PERGINLKA EGY MAR OMN TUN NIC TUR CHN ETH KWT ZWE THA PRT RUS IND SVK CZE ISR TGOCOG BHR HUN IRL PAK DEU MWI SEN MEX COL DOM TTO CMR ARG CHL ALB ESP BRN JPN DZA ARE ECU CUB KEN TWN URY CIV BGR CRI ITA AUT GBR AUS CAN CHE DNK LUX FIN ISL AGOGAB MOZ VEN ZAF USA NOR SWE NLD NZL PNG SAU SGPFRA BEL IRQ BFA PRK BRABWA MYS MDG LBR NER Rate of change SLE GNB CHL BGD PAN ETH ARE PER URY SUR BOL ZMB PHL MEX BHS IRQ HND DZA PAK UGA AUT AGO ESP SGP CYP AUS CAN DNK FIN IND ISL MDG SAU QAT KWT MLT LUX MWI BWA FRAGBR GTM GIN IDN MAR MYS NOR NLD NZL SDN SLV TZA SWE ISR IRL LKA TTO TUN VNM PRT NER ARG BEL DEU ECU BFA LBN BRN CHE MLI GMB CZE COL GUYMNG OMN TWN USA RUS ZAR KOR JPN EGY CUB CHN COG GAB SEN ROM JAM NIC SYR TUR CMR GHA BHR JOR ITA SVKPOL TGO MMR ALB BRA CRI GRC HUN MOZ IRN NAM NGA PRK PNG BGR DOM SOM YEM LBY HTI ZAF THA PRY KEN VEN CIVZWE -.1 SLE SOM Quality of Gov Quality of Gov BOL Rate of change SLV IRN GTM GUY GNB PER BGD GHA PHL NGA ZWE NIC MLI HND SYR ZAR UGA HTI COG MLT JOR PAN TUN JAM PAK LKA DZA COL MAR CYP ZMB ROM POL MWI KORZAF CHL MMR ARG IND GRC TGO CAF MDG GABTTO OMN CRI URY PRY KWT BEN TCD BDI BHR BRA ARE DOM MEX CIV EGYPNG BHS THA TZA ALB SEN ECU IDN BRB CMR TUR NER KEN VEN SLE IRL PRT GBR HKG ESP MUS HUN MYS BWA ISR CZE ITA CHN SWE DEU SGP JPN FRA TWN BGR AUS CAN DNK NZL FIN AUT NOR CHE LUX NLD ISL USA BEL Legal System and Prop. Rights 1985 Rate of change RWA RUS BRB SLE COL NER BHS GNB COG IDN DZA ZAR KEN ALB CHN KOR TUN ARE SEN LKAPER TUR UKR UGA EGYFJI CRI BHR LTU CYP BWA EST JAM BLZ JOR LVA KWT OMN MWI THA TZA ROM CHL IRN BEN GTM GUY GHA CZE FRA HKG NIC ZMB ZAF IND MYS TWN MLT SGP ISL PHLMEX TTO HRV URY NAM SWE BRA AUT DOM BEL CAN AUS DNK ECU JPN GBR CHE NOR NZL SYR PAN SVKPOL FIN BGR ITA MUS LUX DEU NPL NGA PNG GAB MAR NLD PRY HND ESP GRCISR HUN IRL PAKMLI SLV ARG SVN PRT USA CMR BDI BGD VEN MMR BOL MDG HTI TCD ZWE CIV TGO CAF Legal System and Prop. Rights 1995 Figure 3 Initial level of institutional quality vs. subsequent rate of change: pre- and post-cold War 6 The end of the Cold War as a state of political and military tension between the USA and the USSR dates back to 3 rd December 1989, when the American and Soviet leaders declared its end at the Malta Summit. However, the USSR officially dissolved on 25 th December

20 In table 6, the tests are repeated by estimating the convergence regressions over the two sub-periods as a system. While in first sub-period the convergence parameter is significant, it becomes insignificant in the following sub-period. This approach also allows testing the linear restriction that the convergence parameter is the same in both periods. An F- test strongly rejects the null in both cases. These results show that, when splitting the period, the convergence process seems to run out of steam after the mid 199s. 7 Table 6: Convergence in institutional quality pre- and post-cold War, system estimation System 1 System 2 Quality of Quality of Quality of Legal Government, Government, System and Property Rights, Initial value, *** -.9*** (.13) (.1) Initial value, (.8) (.1) Constant.84*** -.9*.66*** -. (.8) (.5) (.7) (.5) F-stat 73.28*** ***.41 Adj. R-Sq Obs RMSE Quality of Legal System and Property Rights, Breusch-Pagan test Chi 2 (1) =.483, P-value =.487 Chi 2 (1) = 3.943, P-value =.47 of independence H: β1985=β1995 F(1,236) = 45.17, P-value =. F(1,216) = 28.74, P-value =. Notes: Each pair of equations is estimated by Seemingly Unrelated Regressions. The dependent variables are the and the growth rate of Quality of Government in columns 1 and 2, and the and the growth rate of the Quality of Legal System and Security of Property Rights in columns 3 and 4. Symbols *, ** and *** stand for significant at 1, 5 and 1% respectively, two-tailed test. The final step of our empirical strategy, in order to document whether after 1995 the convergence process is breaking with the past, is pooling together the cross-sections from the two sub-periods. Such approach allows testing for a structural change in the convergence parameters over time (apart from benefitting from a gain in degrees of freedom). In this case, it means exploiting a two-period panel where a time dummy would identify the pre- and post- Cold War periods. A modified test equation for institutional quality convergence is then: g it = α + β 1 G it + β 2 t + β 3 tg it + α i + ε it with i=1,..., N and t=,1 (2) The dependent variable in this case is the average annual growth rate in institutional quality over each of the two sub-periods and t is the time dummy, which takes value one to identify 7 The results are similar even when stretching the period under scrutiny from 198 to 29, which is possible when using the Quality of Legal System and Security of Property Rights index, so conducting tests on the subperiods and , but on ninety countries only. 2

21 the post-cold War period ( ) and value zero corresponds to the period leading to the end of the Cold War ( or ). According to (2), the sign and magnitude of the effect of initial institutional quality on its subsequent growth depends on the historical period. Hence, the marginal effect will be β 1 + β 3 t. Our conjecture is that β 1 is negative and β 3 is positive. Table 7: Convergence in institutional quality pre- and post-cold War, panel estimation Panel (a): Quality of Government index, and Pooled OLS Fixed Effects Random Effects Initial value -.111*** -.287*** -.116*** (.15) (.2) (.15) Time dummy -.89*** -.29** -.8*** (.14) (.13) (.14) Initial value x Time.99***.29*.84*** (.19) (.16) (.19) Constant.84***.177***.87*** (.1) (.11) (.1) F-stat or Chi-Sq *** *** 24.61*** R-Squared Obs Countries RMSE H: β1+β3= (p-value) β1+β *** -.32*** (.1) (.29) (.12) Panel (b): Quality of Legal System & Property Rights index, and Pooled OLS Fixed Effects Random Effects Initial value -.1*** -.27*** -.11*** (.1) (.1) (.1) Time dummy -.54*** -.14** -.41*** (.11) (.6) (.8) Initial value x Time.7***.3***.5*** (.2) (.1) (.1) Constant.67***.157***.77*** (.9) (.7) (.6) F-stat or Chi-Sq *** *** *** R-Squared Obs Countries RMSE H: β1+β3= (p-value).8.. β1+β3 -.2*** -.25*** -.6*** (.1) (.2) (.1) Panel (c): Quality of Legal System & Property Rights index, and Pooled OLS Fixed Effects Random Effects Initial value -.8*** -.18*** -.9*** (.1) (.1) (.1) Time dummy -.41*** -.14** -.33*** (.9) (.6) (.6) Initial value x Time.5***.2**.4*** (.1) (.1) (.1) Constant.53***.16***.63*** (.6) (.6) (.5) F-stat or Chi-Sq *** *** 24.54*** R-Squared Obs Countries RMSE H: β1+β3= (p-value).8.. β1+β3 -.2*** -.16*** -.6*** (.1) (.2) (.1) Notes: The dependent variables are the and the growth rate of Quality of Government in columns 1 and 2, and the and the growth rate of the Quality of Legal System and Security of Property Rights in columns 3 and 4. Symbols *, ** and *** stand for significant at 1, 5 and 1% respectively, two-tailed test. Standard errors, in parentheses, are robust for arbitrary heteroskedasticity and clustering at the country level. Table 7 presents Pooled OLS, Fixed Effects and Random Effects estimates. Panel (a) refers to Quality of Government. Panel (b) refers to the Quality of Legal System and Security of Property Rights data, over the period Panel (c) uses the same index, but over 21

22 the longest period, i.e., In line with our expectations, the estimates unambiguously suggest that the convergence effect is significant, but it has been weaker after However, while pooled OLS and Random Effects estimates are similar in magnitude, Fixed Effects regressions estimate a much stronger convergence effect. 8 How can we interpret such differences? Which estimates are closer to the true convergence effect? The complement to the evidence from cross-section regressions, which estimate longrun relationships, is a panel approach exploiting within country variation, which investigates the short-run behavior of the relationships under scrutiny. A causal link between initial conditions and growth in institutional quality suggests that we should also see a relationship between their respective changes. This means asking whether growth in institutional quality becomes higher when its initial conditions change. To answer this question, one has to investigate whether the cross-sectional relationship between the variables of interest disappears when country fixed effects are included in the regression, thus removing the longrun determinants of both variables. In this case, Fixed Effects estimates confirm the crosssection results, but seem suspiciously large in magnitude. Since the dependent variable has its principal variation in time (rather than across countries), while all the important variation in the explanatory variable is across countries, Fixed Effects estimates may be shoehorning the data on growth in institutional quality and its initial level into a spurious relationship with each other. 9 In particular, econometric methods that condition out individual effects may overestimate, in magnitude, the impact of initial institutional quality. 1 8 For example, according to panel (b) Fixed Effects estimates, in countries when the initial value of Quality of Property Rights and Legal System index increases by one point, the subsequent average annual growth rate is 2.7 percentage points lower in the period and 2.5 points lower in the following period (as a result of the interaction effect). Similarly, according to panel (a), when the initial Quality of Government index moves from zero (its lowest score) to one (its highest score), its average annual growth is 28.7 percentage points higher in the same period and 25.7 points in the subsequent period. 9 The proportion of the total variation in the initial value of the Quality of Government index due to the between variation is 88 per cent and the same proportion of total variation of its growth rate is, instead, 39 per cent. 22

23 On the other hand, Random Effects estimator uses both sources of variation efficiently, by calculating a weighted average of both between and within variation. However, the risk is that Random Effects estimates could be biased and inconsistent. In particular, the convergence effect could biased toward zero if country-specific effects or time-invariant factors omitted from the regressions, such as quality of state organisation and political tradition, are positively correlated with initial institutional quality and its subsequent growth. 11 Finally, Pooled OLS results are a benchmark, since they use within and between variations inefficiently. Since the variance of the unobserved effects is relatively small and T is only two, Random Effects estimates are relatively close to Pooled OLS (and to the cross-section) results. To summarise, panel results are useful as a robustness check to cross-section results and, above all, to test the constancy of the convergence parameters over time. However, while confirming the quality of the relationships estimated in cross-section regressions, it is not clear whether a panel approach can give more reliable estimates of the speed of convergence. An educated guess would be that the true value of the convergence parameters lies somewhere between Fixed and Random Effects estimates. 12 Similarly, the fraction of total variation in the initial value of the Quality of Property Rights and Legal System index due to the variation across countries is 87 per cent, while for its growth rate is 4 per cent. 1 Quah (23) first raised similar issues in the context of the literature on inequality and growth. This is a special case of spurious regression that econometric theory has now begun to formalise (Choi 211). 11 Hausman tests on whether the difference between Fixed Effects and Random Effects estimates is not systematic (due to error) reject the null in all cases, so favouring Fixed over Random Effects models. 12 The econometric strategy has been to let the data speak for themselves on the specific issue of convergence. In this spirit, the aim of the paper was not to explain the variation in growth of institutional quality or to provide a comprehensive investigation on the determinants of institutional change. However, one may wonder whether the effect of initial institutional quality on its subsequent growth is due to some other factor not included in the regressions. We experimented with time-varying controls, choosing initial level of per capita GDP and the initial level of human development (as building strong institutions can be a function of economic and social development), as well as the initial level of education (measured by the secondary enrolment rate, as it can be positively related designing and functioning institutions). We controlled for other time-invariant variables as well: regional dummies, distance from the equator (to capture any geographical effects), the fraction of population speaking English and the fraction of population speaking another main European language as mother tongue (as proposed in Hall and Jones (1999)). As a result, we found that both panel and cross-section results are robust. 23

24 4.3 Discussion The cross-country regressions presented here are a first pass to understand the evolution of institutional quality around the world. The evidence supports the conjecture that historical events due to the end of the Cold War were accompanied by a wave of institutional quality improvements in the developing world. This started a (slow) convergence process, which seems to have (further) slowed down in the new millennium. Such results should be interpreted as empirical regularities, which are nonetheless robust to different measures of institutional quality. The convergence regressions show that institutions evolve slowly, therefore going against the tenet of the New Institutional Economics, where superior institutional arrangements replace less efficient ones. Instead, the view put forward by Acemoglu and Robinson (26 and 28) that institutions are persistent, and even when inefficient may be kept in place as they serve the interests of influential minorities, tends to be supported by our results. Institutions may change as a result of epochal historical events, as argued in Acemoglu et al (21). In the case of the end of the Cold War, our results suggest, instead, that the building up to the demise of command economies was accompanied by a greater convergence effect than during the period after its end. Although apparently surprising, this seems compatible with the view that Institutional mono-cropping, as adoption of Westernstyle institutions in the South, may not have been as successful as expected due to developing economies-specific constraints (Roland 24; Rodrik 28; Khan 212; Chang 27). From the econometric point of view, our approach relied on cross-section and panel convergence regressions aiming at capturing mean reversion phenomena in institutions. As some literature on national income convergence has emphasised a different statistical notion of convergence (e.g., Quah 1993), a separate avenue for future research could be to focus on 24

25 the cross-section dispersion across countries and whether it is decreasing. Incidentally, note that the decline in cross-sectional dispersion illustrated above already provides some evidence consistent with this idea (and with our regressions). However, the focus of this paper has been on whether initial conditions matter for differences in institutional quality across countries, as this is a question on mean reversion and it is interesting in itself, (what Sala-i-Martin (1996) calls classical convergence, in the context of income convergence). Knowing that institutional quality in poor economies would catch up with that of rich economies could have repercussions on current disparities in income and on other development outcomes. 5. Conclusions With the end of the Cold War, developing economies experienced improvements in institutional quality, reducing the gap with advanced economies. Convergence regressions support this hypothesis, finding evidence of slow convergence in institutional quality from the mid 198s to the mid 199s. There is a significant negative correlation between the initial institutional quality measure and the subsequent change in the index. However, we find that there is less persuasive evidence of convergence in institutional quality observed since the mid 199s. It is not clear why the process of convergence in institutional quality observed across countries in the period till the mid 199s had weakened considerably since the mid 199s. But this does suggest that the positive effect of the end of the Cold War on institutional quality convergence was temporary and had weakened in the new millennium. The relative lack of convergence in institutional quality since the mid 199s suggests the lack of absolute convergence in per capita incomes observed in the twentieth century (Pritchett 1997) may well persist for some time to come in the twenty-first century. 25

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27 Khan, Mustaq, 212. Governance and growth: history, ideology and methods of proof. In Noman, Akbar, Botchwey, Kwesi, Stein, Howard, Stiglitz, Joseph, (eds.), Good growth and governance in africa, Oxford: Oxford University Press, pp Knack, Stephen, Keefer, Philip, Institutions and economic performance: cross-country tests using alternative institutional measures. Economics and Politics 7(3), La Porta, Rafael, Lopez-de-Silanes, Florencio, Shleifer, Andrei, 28. The economic consequences of legal origins. Journal of Economic Literature 46(2), Mkandawire, Thandika, 212. Institutional monocropping and monotasking in Africa. In Noman, Akbar, Botchwey, Kwesi, Stein, Howard, Stiglitz, Joseph, (eds.), Good Growth and Governance in Africa, Oxford: Oxford University Press, pp Pritchett, Lant, Divergence, big time. Journal of Economic Perspective 11(3), Quah, Danny, 23. One third of the world s growth and inequality. In Eicher, Theo, Turnovsky, Stephen J., (eds), Growth and Inequality: Issues and Policy Implications, Cambridge: MIT Press, pp Quah, Danny, Galton s Fallacy and tests of the convergence hypothesis. Scandinavian Journal of Economics, 95, Rodrik, Dani, 28. Second-best institutions. American Economic Review: Papers & Proceedings, 98(2), Rodrik, Dani, Subramanian, Arvind, Trebbi, Francesco, 24. Institutions rule: the primacy of institutions over geography and integration in economic development. Journal of Economic Growth, 91: Roland, Gérard, 24. Understanding institutional change: fast-moving and slow-moving institutions. Studies in Comparative International Development 38(4), Sala-i-Martin, Xavier X, The classical approach to convergence analysis. The Economic Journal, 16(437), Sonin, Konstantin, 23. Why the rich may prefer poor protection of property rights. Journal of Comparative Economics, 31, Stiglitz, Joseph, Broader goals and more instruments: towards the post-washington consensus, UNU-WIDER Annual Lecture, Helsinki. Teorell, Jan, Sören, Holmberg, Bo, Rothstein, 28. The quality of government dataset, version 6 th April 211. University of Gothenburg: The Quality of Government Institute. Available at Williamson, Oliver E., The Mechanisms of Governance. New York, Oxford: Oxford University Press. World Bank, Governance and Development. Washington D.C.: World Bank. World Bank, 211. Worldwide Governance Indicators (WGI) project. Available at: 27

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29 Appendix Table A1: List of countries Developing economies MOROCCO MAR Cyprus CYP ANGOLA AGO MADAGASCAR MDG Germany DEU United Arab Emir. ARE Maldives MDV Denmark DNK ARGENTINA ARG MEXICO MEX Spain ESP BURUNDI BDI MALI MLI Finland FIN BENIN BEN MYANMAR MMR France FRA BURKINA FASO BFA Mongolia MNG United Kingdom GBR BANGLADESH BGD Mozambique MOZ Greece GRC Bahrain BHR MAURITANIA MRT Hong Kong HKG BAHAMAS BHS MAURITIUS MUS Ireland IRL BELIZE BLZ Malawi MWI Iceland ISL BOLIVIA BOL MALAYSIA MYS Israel ISR BRAZIL BRA Namibia NAM Italy ITA Bhutan BTN NIGER NER Japan JPN Botswana BWA NIGERIA NGA Korea KOR CENTRAL AFRICAN REPUBLIC CAF NICARAGUA NIC Luxemburg LUX CHILE CHL Nepal NPL Malta MLT IVORY COAST CIV Oman OMN Netherlands NLD CAMEROON CMR PAKISTAN PAK Norway NOR CONGO COG PANAMA PAN New Zealand NZL COLOMBIA COL PERU PER Portugal PRT Comoros COM Philippines PHL Singapore SGP Cape Verde CPV PAPUA NEW GUINEA PNG Sweden SWE COSTA RICA CRI PARAGUAY PRY Taiwan TWN Cuba CUB Qatar QAT United States USA DJIBOUTI DJI RWANDA RWA Transition economies Dominica DMA Saudi Arabia SAU Albania ALB DOMINICAN REPUBLIC DOM SUDAN SDN Armenia ARM ALGERIA DZA SENEGAL SEN Azerbaijan AZE ECUADOR ECU Solomon islands SLB Bulgaria BGR EGYPT EGY SIERRA LEONE SLE Bosnia-Herzegovina BIH Eritrea ERI EL SALVADOR SLV Belarus BLR ETHIOPIA ETH Sao Tome and Principe STP China CHN FIJI FJI SURINAME SUR Czech Rep. CZE GABON GAB Swaziland SWZ ESTONIA EST GHANA GHA Seychelles SYC Georgia GEO GUINEA GIN Syria SYR Croatia HRV GAMBIA GMB CHAD TCD Hungary HUN GUINEA-BISSAU GNB TOGO TGO Kazakhstan KAZ GNQ Thailand THA Kirghizstan KGZ Grenada GRD Tonga TON Cambodia KHM GUATEMALA GTM TRINIDAD AND TOBAGO TTO LAOS LAO GUYANA GUY TUNISIA TUN LITHUANIA LTU HONDURAS HND Turkey TUR LATVIA LVA HAITI HTI TANZANIA TZA Moldova MDA INDONESIA IDN UGANDA UGA Macedonia MKD INDIA IND URUGUAY URY Poland POL Iran IRN St. Vincent & Grenadine VCT North Korea PRK JAMAICA JAM VENEZUELA VEN Romania ROM Jordan JOR Vanuatu VUT Russia RUS Yemen YEM Slovak Rep. SVK KENYA KEN SOUTH AFRICA ZAF Slovenia SVN Kiribati KIR Zambia ZMB Tajikistan TJK St. Kitts & Nevis KNA Zimbabwe ZWE Ukraine UKR Kuwait KWT Advanced economies Uzbekistan UZB Lebanon LBN AUSTRALIA AUS VIETNAM VNM Libya LBY Austria AUT St. Lucia LCA Belgium BEL SRI LANKA LKA Canada CAN Lesotho LSO Switzerland CHE 29

30 Table A2: Definition of the variables Panel (a): Fraser Institute (Gwartney and Lawson 27) Quality of This variable includes: Legal System (a) Judicial independence: the judiciary is independent and not subject to and Security interference by the government or parties in dispute. This component is from the of Property Global Competitiveness Report s question: Is the judiciary in your country Rights independent from political influences of members of government, citizens, or firms? No heavily influenced (=1) or Yes entirely independent (=7). Source: World Economic Forum, Global Competitiveness Report (various issues), at (b) Impartial courts: a trusted legal framework exists for private businesses to challenge the legality of government actions or regulation. This component is from the Global Competitiveness Report s question: The legal framework in your country for private businesses to settle disputes and challenge the legality of government actions and/or regulations is inefficient and subject to manipulation (=1) or is efficient and follows a clear, neutral process (=7). (c) Protection of property rights. This component is from the Global Competitiveness Report s question: Property rights, including over financial assets are poorly defined and not protected by law (=1) or are clearly defined and well protected by law (=7). (d) Military interference in the rule of law and the political process (from ICRG); this component is based on the International Country Risk Guide s Military in Politics: In the short term a military regime may provide a new stability and thus reduce business risks. However, in the longer term the risk will almost certainly rise, partly because the system of governance will be become corrupt and partly because the continuation of such a government is likely to create an armed opposition. Source: PRS Group, International Country Risk Guide (various issues), (e) Rule of law (from ICRG, see above): it is defined as integrity of the legal system, i.e., strength and impartiality of the legal system and popular observance of the law. (f) Legal enforcement of contracts. This component is based on the World Bank s Doing Business estimates for the time and money required to collect a clear-cut debt. The debt is assumed to equal 2% of the country s per-capita income where the plaintiff has complied with the contract and judicial judgment is rendered in his favor. Source: World Bank, Doing Business (various issues), (g) Regulatory restrictions on the sale of real property. This sub-component is based on the World Bank s Doing Business data on the time and monetary costs required to transfer ownership of property that includes land and a warehouse. Source: World Bank, Doing Business (various issues), Panel (b): ICRG measures (ICRG 1997) Bureaucratic quality Rule of law Corruption in government Expropriation risk Government repudiation of contracts High scores indicate "an established mechanism for recruitment and training," "autonomy from political pressure," and "strength and expertise to govern without drastic changes in policy or interruptions in government services" when governments change. This variable, also known as Law and Order Tradition, "reflects the degree to which the citizens of a country are willing to accept the established institutions to make and implement laws and adjudicate disputes." Higher scores indicate: "sound political institutions, a strong court system, and provisions for an orderly succession of power." Lower scores indicate: "a tradition of depending on physical force or illegal means to settle claims." Upon changes in government new leaders "may be less likely to accept the obligations of the previous regime." Lower scores indicate "high government officials are likely to demand special payments" and that "illegal payments are generally expected throughout lower levels of government" in the form of "bribes connected with import and export licenses, exchange controls, tax assessment, police protection, or loans." The full name is Risk of expropriation of private investment. This variables evaluates the risk "outright confiscation and forced nationalization" of property. Lower ratings "are given to countries where expropriation of private foreign investment is a likely event." The full name is Risk of Repudiation of Contracts by Government. This indicator addresses the possibility that foreign businesses, contractors, and consultants face the risk of a modification in a contract taking the form of a repudiation, postponement, or scaling down" due to "an income drop, budget cutbacks, indigenization pressure, a change in government, or a change in government economic and social priorities." Lower scores signify "a greater likelihood that a country will modify or repudiate a contract with a foreign business." Panel (c): Quality of Government, Teorell et al. (28) Quality of Government Panel (d): World Governance Indicators (World Bank 21) Government effectiveness Rule of law Control of Corruption Regulatory quality The mean value of the ICRG variables Corruption in Government, Law and Order and Bureaucracy Quality, scaled -1. Higher values indicate higher quality. This variable captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. This variable captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. This variable captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests. This variable captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. 3