The Political Economy of Heterogeneous Development: Quantile Effects of Income and Education

Transcription

1 This wrk is distributed as a Discussin Paper by the STANFORD INSTITUTE FOR ECONOMIC POLICY RESEARCH SIEPR Discussin Paper N The Plitical Ecnmy f Hetergeneus Develpment: Quantile Effects f Incme and Educatin By Marcus Alexander Harvard University Matthew Harding Stanfrd University Carls Lamarche University f Oklahma August 2008 Stanfrd Institute fr Ecnmic Plicy Research Stanfrd University Stanfrd, CA (650) The Stanfrd Institute fr Ecnmic Plicy Research at Stanfrd University supprts research bearing n ecnmic and public plicy issues. The SIEPR Discussin Paper Series reprts n research and plicy analysis cnducted by researchers affiliated with the Institute. Wrking papers in this series reflect the views f the authrs and nt necessarily thse f the Stanfrd Institute fr Ecnmic Plicy Research r Stanfrd University.

2 The Plitical Ecnmy f Hetergeneus Develpment: Quantile Effects f Incme and Educatin Marcus Alexander, Matthew Harding and Carls Lamarche August 2008 Abstract Des develpment lead t the establishment f mre demcratic institutins? The key t the puzzle, we argue, is the previusly unrecgnized fact that based n quantitative regime scres, cuntries ver the past 50 years have clustered int tw separate, very distinct, yet equally-cmmn stages f plitical develpment authritarian states with lw levels f freedm n ne side and demcracies with liberal institutins n the ther side f a bimdal distributin f plitical regimes. We develp a new empirical strategy expliting exgenus wrld ecnmic factrs and intrducing new panel data estimatrs that allws fr the first time t estimate the effects f develpment as well as changing unbserved cuntry effects in driving demcracy at these different stages f plitical develpment. We find that incme and educatin have the least effect n demcracy when authritarian regimes are cnslidated and that nly changing cuntry effects, pssibly accunting fr institutinal legacies, can lead t plitical develpment. Irnically, it is in highly demcratic and wealthiest f natins that incme and educatin start t play a rle; hwever greater wealth and better educated citizenry can bth help and hurt demcracy depending again n what the cuntry s institutinal legacies are. Far frm accepting the ntin that much f the develping wrld is cursed by unchanging and pr lng-run institutins, plicy-makers shuld take nte that with demcratizatin we als see changing cuntry-specific factrs that in turn cnditin the difference incme and educatin make fr demcracy. JEL: C13, C23, P16, O10 Keywrds: demcracy, ecnmic develpment, quantile regressin We are grateful t Tim Hyde fr excellent research assistance. We are grateful t Rbert Bates, Victr Chernzhukv, Jrge Dminguez, Dawn Brancati, Margarita Estavez-Abe, Kevin Grier, Yshik Herrera, Nahmi Ichin, Trben Iversen, Gary King, Rderick MacFarquhar, Thmas Remingtn, James Rbinsn and seminar participants at Harvard and Stanfrd fr useful cmments, and t Darn Acemglu, James Rbinsn, Simn Jhnsn and Pierre Yared fr sharing their histrical data. Institute fr Quantitative Scial Science, Harvard University, 1737 Cambridge Street, Cambridge, MA 02138; malexand@fas.harvard.edu Department f Ecnmics, Stanfrd University, 579 Serra Mall, Stanfrd, CA 94305; Phne: (650) ; Fax: (650) ; mch@stanfrd.edu Department f Ecnmics, University f Oklahma, 729 Elm Avenue, Nrman, OK 73019; Phne: (405) ; lamarche@u.edu

3 2 1. Intrductin Western histry is ften presented as the struggle f freedm and demcracy against the frces f authritarian gvernment, ging back as far as Herdtus wh used this argument t mtivate the clash between the Hellenes and the Persians. Tday demcracy is als assciated with ecnmic prsperity as plitical and ecnmic develpment appear t be psitively crrelated ver lng perids f time. The failures f mdern ttalitarian regimes in Germany, Russia and China had fueled hpe fr prpnents f demcracy, as the last 50 years have seen stunning changes in the plitical landscape, frm the Eurpean clnies achieving independence t the fall f the Berlin Wall. Yet, a recent reprt by the Freedm Huse, a US based nngvernmental rganizatin (NGO), dcuments the reversal f the trend twards demcracy in 38 cuntries, particularly in Asia and Africa. Mrever, nly tw cuntries, Thailand and Tg have made any prgress twards demcracy in recent years. We shw in this paper that far frm being defined by the grwing dminance f demcracy, the secnd part f the 20th century was characterized by the entrenchment f tw very distinct, yet equally cmmn plitical regime types liberal demcracy guaranteeing plitical rights n ne hand and autcracies characterized by pr institutins and lack f plitical and civil rights n the ther. Analyzing the tw mst well-knwn and reliable indicatrs f regime type fr all cuntries in the wrld since the Secnd Wrld War, we find that the distributin f plitical regimes in the wrld fllws a bimdal distributin. The bimdal distributin f regime types in the wrld has nt been previusly empirically dcumented r explained. In additin t dcumenting the existence f regime clustering int tw ppsite types, here we als shw that understanding the causes f the bimdal regime distributin hlds the key t answering the questin f whether develpment can bring abut demcracy. This questin is at the tp f internatinal plicy-making agenda, frm the Wrld Bank trying t imprve institutins that maximize transparency and accuntability t Western gvernments freign plicies emphasizing supprt fr demcracy as bth a human rights and an internatinal security imperative. The success f bth Wrld Bank and natinal gvernments in prmting demcracy in large part rests n discvering whether prmting develpment can bring abut demcracy; here, we will shw that this questin can be understd by analyzing and explaining why is that all cuntries in the wrld have clustered int tw distinct, ppsite regime types ver the past half century. While ecnmists have emphasized the imprtance f demcracy stimulating ecnmic grwth (Perssn and Tabellini, 1997, 2000, 2003; Perssn et. al. 2000), we must als address the questin f whether ecnmic develpment can stimulate plitical develpment. The questin f hw incme affects demcracy has nly recently captured the attentin f ecnmists. In this paper, we fcus n tw ptential frces f develpment, incme and educatin, and assess the extent t which they can facilitate the struggle fr civil and plitical liberties, as well as the establishment f liberal demcratic institutins that preserve thse liberties in the lng run. This is relatively unexplred territry fr ecnmists, wh first directed their attentin t this prblem after Barr (1999) shwed that a number f develpment indicatrs such as imprvements in living

4 3 standards, especially GDP and educatin, reduced dependence n natural resurces, middle-class share f incme and certain religins affiliatins are mre cnducive t demcratizatin. Many f the issues discussed in this study have been mentined in sme frm r anther in the vast plitical science literature f the past 50 years, but were apprached frm a less quantitative perspective. The earliest systematic frmulatin f the cnnectin between plitical and ecnmic develpment is due t Lipset (1959, 1963). T explain the bimdal regime distributin and the underlying effect that develpment has n this distributin, we had t develp a new empirical strategy that simultaneusly slves the prblems f (1) reverse causality given that it is well established that institutins affect develpment; (2) unbserved hetergeneity and lng-run cuntry-specific effects given that n set f indicatrs in any cmparative study can accunt fr all cuntry differences in institutins, culture and histrical legacies that culd affect demcracy; and (3) the fact that all existing empirical strategies in the literature can nly be used t estimate the effect f incme n the mean f demcracy, which may be uninfrmative given that we demnstrate that regimes are distributed bimdally. Our empirical strategy invlves using three different sets f instruments that identify exgenus variatin in incme but are presumably nt crrelated with demcracy. Tw f these instruments (gegraphy and trade) have been used in the literature previusly, while ur third and preferred set f instruments is based n a new strategy f using shcks t wrld markets measured by estimating glbal factrs. We slve the secnd and third challenges abve by designing several new estimatrs that can enable us t measure the effect f develpment at different quantiles f demcracy distributin, while at the same time allwing us t identify changing cuntry-specific factrs that stand in fr lng-run institutins, culture and histrical legacies. Therefre, the entirely new empirical apprach is t estimate IV quantile effects as well as unbserved hetergeneity bth at cuntry-specific and distributin-specific levels. The starting pint fr ur study therefre is the finding that the distributins f tw cmmnly used numerical measures f demcracy are bimdal with mst cuntries cncentrated at the extremes. This mtivates ur methdlgy as a departure frm traditinal mean regressin techniques and instead re-rient the tpic f the discussin n the estimatin f different effects f the variables f interest at different quantiles f the demcracy distributin. Adding ur three sets f instruments, we identify the effect f ecnmic develpment that is strnger in the middle range f the distributin and almst nn-existent in the tails. In practical terms we find that ecnmic develpment has a three t fur times larger impact in Latin America than in Sub-Saharan Africa. This finding lends supprt t an emerging fcus n s-called hybrid demcracies, regimes that have spent years r even decades in-between the perid f a cllapsed dictatrship and a full-fledged demcracy, including many African, Asian and Eastern Eurpean cuntries after the fall f cmmunism. Being acutely aware f the difficulties typically encuntered by applied researchers in finding valid instruments, we shw that similar results hld when we use a set f gegraphic instruments, an instrument based n wrld trade, and a set f instruments designed t capture wrld ecnmic factrs. These inverted U-shaped relatinships between incme and demcracy and between schling and demcracy

5 4 ver the quantiles f the distributin f demcracy are fund t be rbust t a number f ecnmetric specificatins. Hwever, ur mst significant finding arises nly when we estimate changing cuntry-specific effects. Fr the first time in the literature, we allw fr the estimatin f different effects that are nt nly cuntry-specific but that furthermre are allwed t vary acrss the distributin f demcracy. We find that nce we accunt fr cuntry-specific effects, the inverted U-shaped relatinship described abve disappears. In fact, fr the lw quantiles f the demcracy distributin, the effect f incme and schling n demcracy is very clse t zer. Hence, the answer t the questin f whether develpment can prmte the establishment f demcracy in autcratic regimes is n. Having fund that cuntry specific effects matter disprprtinately mre than ecnmic develpment in determining demcracy, we ask whether this is unifrmly s ver the distributin f demcracy. The analysis suggests, hwever, that the imprtance f these factrs diminishes as cuntries becme mre demcratic. Even fr demcratic cuntries, hwever, we find evidence f ecnmic develpment playing a hetergeneus rle, a fact cnsistent with a large literature emphasizing institutinal differences in mdern demcracies (Lijphart, 1999; Hall and Sskice, 2001). Institutinal differences are well knwn t explain different crsscuntry differences in ecnmic perfrmance, particularly in the case f labr market utcmes (Blanchard, 2004). Mre recently differences in labr market institutins have been explained by differences in civic virtues acrss cuntries that jintly determine bth plitical and ecnmic utcmes (Algan and Cahuc, 2008). In this paper, we find that the cuntry specific effects measured by the ecnmetric mdel are a cmbinatin f lng-run institutinal factrs and cntemprary circumstances such as military cups r cnstitutinal refrms. Our paper cmplements the recent quantitative wrk f Acemglu et. al. (2008), which analyzes similar data within the cntext f a mean regressin framewrk and ur findings are bradly cnsistent with theirs. Our quantile regressin framewrk hwever allws us t explre the same issues frm the perspective f increasingly fine granularity and thus direct the discussin t the rle f crss-cuntry hetergeneity and the extent t which statistical relatinships are cnditined by the relative psitin ccupied by a cuntry in the distributin f demcracy. Mre than prviding finer detail, as we address in ur discussin, ur findings call fr rerienting the current debate n incme and demcracy. Demcracy in ur analysis emerges as what has been previusly termed a fundatinal gd, r what is even better understd as a fundatinal institutin. We have in fact fund that all cuntry-specific, unmeasured effects can change as cuntries mve twards mre demcratic regimes. Develpment has zer effect, but as demcracy is established, ur evidence suggest that ther lng-run institutins, histrical legacies and culture change. Far frm being fixed and inescapably path dependent, these cuntry effects can change and pen the dr fr ecnmic develpment t further affect plitical regimes. As cuntries becme demcratic, the new set f institutins cnditins the rle that

6 5 wealth and educatin can have n demcracy. Again, far frm having a simple effect, greater wealth can bth prmte and retard demcracy. The structure f the paper is as fllws. In Sectin 2, we intrduce the data and describe the mtivating puzzle f the bimdal distributin f demcracy. Sectin 3 discusses the basic quantile regressin mdel and characterizes the estimated inverted U-shaped relatinship between incme and demcracy ver the quantiles f the incme distributin. Sectin 4 extends the analysis t an instrumental variables framewrk. Sectin 5 intrduces the tw types f unbserved effects and makes the distinctin between lcatin and distributinal shifts n the quantities f interest. Sectin 6 presents evidence n patterns f demcracy and suggests an explanatin fr the puzzle presented in Sectin 2. Sectin 7 cncludes. Appendices A and B prvide details n the cmputatinal aspects f the estimatin methds, and describes the data. The nline appendix available n the Web prvides additinal rbustness checks nt reprted in this versin f the paper. 2. The Puzzle f the Bimdal Distributin We emply tw measures f demcracy fr which data is publicly available, the Plity and Freedm Huse scres. The Plity (versin IV) scre, cmpiled by an academic panel at Gerge Masn University s Center fr Internatinal Develpment and Cnflict Management, is defined as the difference between an index f autcracy and an index f demcracy fr each cuntry. Each gvernment is assigned a number between 0 and 10 n each scale based n a set f weighted indicatrs designed t capture the extent f cmpetitive plitical participatin, institutinalized cnstraints n executive pwer and guarantees f civil liberties and plitical participatin. The primary fcus f the index is n central gvernment and it ntably ignres the extent t which cntrl ver ecnmic resurces is shared and the interactin between central gvernment and separatist r revlutinary grups. We use a sample f cuntries frm 1945 t 1999 nrmalized t range between 0 and 1. The Freedm Huse demcracy scre is cmpiled by a New Yrk based NGO funded by Eleanr Rsevelt and aims t measure the extent f freedm as experienced by individuals. It cnsists f a rating system invlving 10 plitical rights and 15 civil liberties questins. The questins cver diverse categries such as the electral prcess, plitical pluralism and participatin, functining f gvernment, freedm f expressin and belief, assciatinal rights, rule f law and persnal autnmy. By design it places greater emphasis n experienced freedm as ppsed t legal guarantees. We emply a sample nrmalized t a range between 0 and 1. The sample cvers the perid 1972 t 1999.

7 6 In Table 1 and Table 2, in the nline appendix, we list the cuntries in the Plity sample with their crrespnding cuntry cdes and sampling perids. The number f bservatins per cuntry varies substantially with the inclusin f relatively new cuntries such as thse previusly part f the Sviet Unin. In Table 3, in the nline appendix, we present the summary statistics fr the measures f demcracy emplyed in this paper disaggregated by gegraphic regins. In spite f the different cncepts f demcracy that the tw measures are meant t capture, frm a purely numerical pint f view they shw remarkable agreement. As ne wuld intuitively expect, the mean values fr the Western wrld are abut 0.9 while thse fr Sub-saharan Africa are nly abut 0.3. While these tw measures rely n a substantial amunt f subjectivity, they have been used extensively in quantitative studies as measures f plitical freedm (see, e.g., Acemglu et. al., 2008; Barr, 1999; Fearn and Laitin, 2003). On clser cnsideratin f the tw measures f demcracy, perhaps the mst striking feature is their prnunced bimdal distributin as illustrated in Figure 1 fr the Plity measure and Figure 2 fr the Freedm Huse measure. Bth distributins have a mde at 1 and anther mde at 0.1 and 0.2 respectively. The near lack f mass at the mean f the distributin invites the questin as t the usefulness f mean regressin as a quantitative tl fr analyzing the relatinship between incme and demcracy. While we acknwledge that it is difficult t make inferences based nly n the uncnditinal distributin, we cannt but enquire whether the relatinship between incme and demcracy differs at different quantiles f demcracy. Thus, we shall depart frm previus quantitative wrk n this subject and fcus exclusively n results based n a quantile regressin methdlgy. Until nw, few attempts have been made t explain the puzzle behind the bimdal cncentratin f plitical regimes. Recent wrk in plitical science hwever seems t be cnsistent with the emphasis we place n explaining the relatinship between incme and demcracy at different quantiles f demcracy. Przewrksi and Limngi (1997) and Przewrski et. al. (2000) argue that cuntries ften becme demcratic fr reasns which d nt appear t be cnnected t incme, but nce they are demcratic mre prsperus cuntries are mre likely t remain demcratic. Epstein et. al. (2006) highlight the imprtance f partial demcracies, cuntries with fragile demcratic status which tend t be vlatile and highly hetergeneus. These studies appear t pint ut varying mechanism fr plitical develpment as well a hetergeneus relatinship between ecnmic and plitical develpment at different stages f demcratizatin. 3. Measuring Quantile Effects In a typical least-squares regressin mdel apprach t the analysis f the relatinship between incme and demcracy, we fcus n estimating the best linear predictr f the cnditinal expectatin f the dependent

8 7 variable, (3.1) E(D i,t I i,t 1, x i,t ) = γi i,t 1 + x i,tβ, where D i,t is the nrmalized demcracy fr cuntry i at time t. The incme variable I i,t 1 is measured at time t 1. It crrespnds t the lg f per capita GDP. The parameter γ captures the (marginal) effect f incme n demcracy at the mean level. Any additinal cntrls r variables f interest such as educatin r ppulatin are included in the variables x i,t. As we discussed in the previus sectin, the uncnditinal distributin f incme is strngly bimdal with mst cuntries clustered at the ends f the scale. Thus it seems that an analysis fcused n the (cnditinal) mean f the distributin might miss imprtant distributinal effects f incme and that by lking at the tails f the distributin we may uncver richer evidence. Frm an ecnmetric pint f view, a quantile regressin apprach may als be mre rbust t distributinal assumptins n the errr term Pled Quantile Regressin Mdel We shall direct ur attentin t the mdeling f the -th cnditinal quantile functins f demcracy fr cuntry i at time t, (3.2) Q Di,t ( I i,t 1, x i,t ) = γ()i i,t 1 + x i,tβ(). By definitin, the -th quantile f the distributin f demcracy is the value Q D () such that Pr(D Q D ()) =. The quantile crrespnds t the area under the uncnditinal distributin f demcracy, bunded by zer n the left and the value Q D n the right. Thus, a mdel estimated at = 0.5 will prduce evidence n the effect f incme at the median f the demcracy distributin. This mdel, mre cmmnly knwn as a Laplace median regressin, is ften cntrasted with the mean regressin discussed abve. Hwever, ur interest lies in estimating the cnditinal quantile functins at all quantiles f the distributin f demcracy, paying particular attentin t the estimatin f the relatinship in the tails f the distributin, that is where is clse t either 0 r 1. We will restrict ur attentin t a linear specificatin f the cnditinal quantile functins. This mdel can be estimated by slving, (3.3) arg min N i=1 t=1 T ρ (D i,t γ()i i,t 1 x i,t β()), using interir pint methds. The piecewise linear quantile lss functin ρ (u) is defined as ρ (u) = (1{u > 0}+(1 )1{u < 0}) u fllwing Kenker and Bassett (1978). It can be shwn that (γ(), β ()) minimize E[ρ (D i,t γ()i i,t 1 x i,tβ())]. The abve mdel will be referred t as the pled quantile regressin

9 8 mdel, fr althugh it is applied t panel data it des nt estimate individual specific effects and further extensins which will be intrduced belw. We fcus n quantile regressin as an attempt t capture the underlying bserved hetergeneity in the relatinship between demcracy and its determinants such as incme r educatin. Hence we estimate the relatinship at different quantiles f the cnditinal distributin f demcracy fr {0.1, 0, 25, 0.5, 0.75, 0.9}. This design measures the effect at each f the three quartiles and als at the first and last decile. This allws us t gain a cmprehensive view n hw the relatinship changes with the distributin f demcracy. It is imprtant t nte that quantile regressin is nt the same as mean regressin applied t different subsets f the data rdered by the distributin f the dependent variable. Thus, while we estimate the quantile regressin functin at the lw quantile = 0.1 in rder t ascertain the extent t which incme and educatin cnditin demcracy in the lwer tail f the distributin f demcracy, this is very different frm estimating a mean regressin where we cnditin n data in the lw tail f the distributin. Thus, Q Di,t (0.1 I i,t 1, x i,t ) is nt the same as E(D i,t D i,t < c, I i,t 1, x i,t ), fr sme apprpriately chsen c meant t capture the lwer tail f the distributin. In particular it may be the case that the abve mment des nt exist. Furthermre, there is n thery which tells us hw t chse r interpret the parameter c while has a natural interpretatin. Quantile regressin captures the effect f the cvariates at a particular quantile f the distributin f the dependent variable, whereas the abve suggested truncated mean regressin estimates the cnditinal mean in a subsample f the data, ignring the rest f the distributin f the dependent variable. In rder t facilitate cmparisns acrss mdel specificatins and ecnmetric prcedures we present results side-by-side in Tables 1, 2 and 3. Since fr each specificatin quantile regressin delivers nt ne set f estimates but five fr each f the quantiles used, the tables can be interpreted in the fllwing way. Cnsider the mdels presented in Table 1. The first mdel cnsists f the baseline pled quantile regressin described abve. The mdel regresses the Plity Measure f demcracy n the ne perid lagged lg GDP per capita and the lg ppulatin in the current perid. The estimated cefficients at each f the quantiles are given in the first five clumns labeled by the crrespnding quantiles. The last clumn labeled Mean presents the estimated cefficients f a standard mean regressin mst clsely assciated with the quantile regressin prcedure emplyed in the crrespnding quantile mdel. Thus, fr the pled quantile regressin setup this is just OLS n the entire sample. As we shall see belw hwever, nce we take the panel data structure int accunt we shall emply ther prcedures such as fixed effects r instrumental variables fr bth the quantile regressin and the mean regressin. Given the fact that quantile regressin prduces five sets f cefficient estimates fr every mdel it is unavidable t have several related tables which the careful reader will need t navigate. In additin t cntaining infrmatin n different mdel specificatins each table duplicates the

10 9 results fr each f ur tw variables fr the demcracy, the Plity Measure and the Freedm Huse Measure. As is custmary we reprt standard errrs in parenthesis. These were btained using the btstrap. 5 The general prcedure invlves sampling pairs frmed f the dependent variable and the set f independent variables with replacement t accmmdate different frms f heterscedasticity. In ur panel setting, a similar strategy is t first sample pairs f bservatins with replacement, and then randmly sample within grups either with r withut replacement. The first strategy prvides a reliable apprximatin fr the precisin f the estimates when T is relatively large (see, e.g., Davisn and Hinkley 1997). The empirical cvariance matrix can be cmputed given B btstrap estimates f the cefficients. Due t the already dense tables required we shall nt reprt significance fr each quantile cefficient, althugh the reader can easily cmpute the t-statistic in each cell An Inverted U-shaped Relatinship between Incme and Demcracy? We shall nw turn ur attentin t the evidence derived frm the use f quantile regressin as intrduced abve in uncvering the relatinship between incme and demcracy. The pled quantile regressin mdel fr the Plity measure estimates an inverted U-shaped relatinship between incme and demcracy ver the quantiles f the demcracy distributin. Thus in the left tail f the demcracy distributin we estimate a cefficient f at the = 0.1 quantile. The effect increases t at the median f the demcracy distributin and declines t in the right tail f the distributin fr = 0.9. By cntrast the cefficient n lagged GDP per capita is if the mdel is estimated by OLS. Similarly, if we estimate the same pled quantile regressin mdel fr the Freedm Huse measure we estimate a cefficient f at the = 0.1 quantile, at the median quantile and at the = 0.9 quantile. The mean effect f lg GDP n demcracy is These results suggest that a 10% increase in lg GDP per capita increases the demcracy scre f a cuntry in the lwer tail f the demcracy distributin by less than Recall that the difference between the mean demcracy scres f Western cuntries t that f Sub-saharan cuntries is ver 0.6. Thus, incme appears t have a negligible effect n imprving demcracy in cuntries with lw demcracy scres. On the ther hand the impact f incme n demcracy is three t fur times larger in cuntries situated at the median 5 The btstrap and alternative resampling methds fr crss sectinal quantile regressin has been investigated, amng thers, by Buchinsky (1995), Hahn (1995), Hrwitz (1998). 6 Nte that ur estimates f the mean effect are higher than the crrespnding values reprted in Acemglu et. al. (2008). This is due t the different mdel specificatin. We d nt include a lagged dependent variable in ur specificatins fr reasns that will be discussed in Sectin 5.4.

11 10 f the demcracy distributin. In practical terms this means that a 10% rise in incme is likely t have a much larger impact in Latin America than in Sub-saharan Africa. The results lean twards prviding supprt fr the Epstein et. al. (2006) view that incme is a much mre ptent engine f change in hybrid demcracies. In rder t verify that this is indeed a quantile effect and nt driven simply by the presence f cuntries with mre unusual characteristics at specific lcatins within the distributin f demcracy we als ran a number f specificatins where we excluded certain cuntries which may be driving this effect. Thus, we excluded cuntries in Eastern Eurpe and the frmer Sviet Unin, certain African cuntries r Muslim cuntries. In every case hwever we btained a similar inverse U-shape pattern f the estimated cefficients even thugh the cmpsitin f the distributin changed. This indicates that the results d indeed vary ver the distributin f demcracy and are nt driven by the inclusin f certain grups f cuntries. In Table 2 we extend the mdel by adding a schling variable crrespnding t the percentage f the ppulatin in a given year with a secndary educatin. This reduces the effect f incme n demcracy at all quantiles as ne wuld expect given the crrelatin between incme and schling. In the regressins using the Plity measure we als estimate an inverse U-shaped relatinship between schling and demcracy ver the quantiles. The estimated effect increases frm at the = 0.1 quantile t at the median and decreases t at the = 0.9 quantile. Similar results are btained fr the Freedm Huse measure. The inverse U-shaped relatinship was btained frm a pled quantile regressin mdel. We ught t be cncerned, hwever, that the estimated relatinship is nt ecnmetrically rbust due t the lack f exgenus variatin in incme and schling r due t ignred cuntry specific hetergeneity. These issues will be explred in much greater depth in the next sectins where we extend the quantile regressin mdel t take int accunt endgeneity and different specificatins f cuntry effects. Withut ging int extensive details, Table 1 and Table 2 als include quantile regressin results using instrumental variables and cuntry-specific effects. In the next sectin we discuss different chices f instruments and their relative merits. In Tables 1 and 2 we use the IV Set 1 which cnsists f gegraphic variables traditinally assciated with ecnmic develpment: muntainus terrain, gegraphic latitude and the distance t the nearest prt. Using these instruments t accunt fr the ptential endgeneity f GDP in the mdel we estimate the effect f incme n demcracy at the previus quantiles. Fr bth measures f demcracy, we find that qualitatively the results are very similar. The estimated inverse U shape remains and is in fact mre prnunced. Thus, the effect f incme n demcracy falls in the lw and high quantiles and is higher at the median. Fr the Plity, measure the estimated cefficient n the = 0.1 quantile changes frm 0.06 t 0.02, while fr the median it increases frm t The estimated cefficient n the = 0.9 quantile increases slightly frm t

12 11 A similar pattern is bserved fr the Freedm Huse measure and fr the mdel that includes schling. In rder t accunt fr unbserved hetergeneity at the cuntry level we can augment the mdel by including cuntry specific effects. As we will discuss in Sectin 5, in a panel data quantile regressin mdel cuntry effects may imply tw different mdel specificatins depending n whether they act as a lcatin shift r distributinal shift. The results in Table 1 crrespnd t a lcatin shift mdel. We ntice immediately that the inverse U-shape cnfiguratin f the estimated effects disappears altgether. In fact, fr the Plity measure the estimated cefficients are at the = 0.1 quantile, at the median and at the = 0.9 quantile. Once we add cuntry effects the estimated relatinship between incme and demcracy disappears at all quantiles. Althugh ur discussin s far has been fcused n pint estimates it is imprtant t remark that these results cannt be explained away by statistical significance. Fr practical cnsideratins we d nt discuss the significance f the estimates f the cefficients at every quantile. Hwever, it is easy t see that the measured inverse U-shape relatinship is statistically significant fr bth the pled quantile regressin mdel and the IV mdel as the estimated standard errrs are very small at every quantile. The standard errrs increase substantially in the fixed effects mdel implying that the estimated cefficients n incme are either zer r statistically insignificant. Similar results hld fr the estimated cefficients n the schling variable. 4. Instrumental Variables In the previus sectin, we have briefly discussed the ntin that cnditinal quantile functin f Equatin 3.2 may nt capture the desired structural relatinship if the sampling f incme acrss the sample is independent f the errr term. Thus, bth incme and demcracy may be manifestatins f sme ther latent variable nt expressed in the cnditinal quantile functin. This induces nn-randm sampling accrding t the relatinship, (4.1) I i,t = δ(x i,t, z i,t, v i,t ), where z i,t is a vectr f instrumental variables independent f the structural disturbance but related t incme and v i,t is an additinal errr term crrelated with the disturbance f the demcracy equatin. Thus, we relax the assumptin that incme and the individual disturbance are uncrrelated. The idea is familiar frm classical linear ecnmetric techniques where it is knwn that it leads t biased estimates. Similarly, in the quantile regressin setting the biased sampling induces an endgeneity bias in the estimated cefficients. This prblem can be slved with the aid f additinal exgenus variables, knwn as instruments, which are independent f the unberved disturbances but structurally related t incme by the abve reduced frm

13 12 relatinship. We fllw the methd prpsed in Chernzhukv and Hansen (2008). As befre we als assume that the cnditinal quantile relatinship is mntnic in. The bjective functin fr the cnditinal instrumental quantile relatinship is given by: ( )] (4.2) R(, γ, β, µ) = E [ρ D i,t γ()i i,t 1 x i,tβ() µ()îi,t 1, where Î is btained as the linear prjectin f the exgenus variables x and z n the endgenus variable. The estimatin prcedure f Chernzhukv and Hansen (2008) prceeds in tw steps. First we minimize the bjective functin abve fr β and µ as functins f and γ, ) (4.3) (ˆβ(γ, ), ˆµ(γ, ) = argmin β,µ R(, γ, β, µ). Then we estimate the cefficient n the endgenus incme variable by finding the value f γ, which minimizes a weighted distance functin defined n µ: (4.4) ˆγ() = argmin γ ˆµ(γ, ) ˆΩ(γ)ˆµ(γ, ), where ˆΩ(γ) is the inverse cvariance matrix f NT(ˆµ(γ, ) µ(γ, )). Ntice that the expressin abve implies that the prcedure effectively minimizes the Wald statistic f the test µ(γ, ) = 0. S far we have nly discussed the prcedure in terms f incme as the endgenus variable, but it als applies t specificatins which include educatin as an endgenus variable. As Rbinsn (2006) remarks, Acemglu et. al. (2008) are the first nes t prpse an instrumental variable apprach t the identificatin f the causal effect f incme n demcracy. Since their prpsed instruments are nt uncntrversial we shall explre sme alternatives belw Gegraphic Instruments While the plitical science literature n demcratizatin seems t have ignred the ptential endgeneity f incme in this specificatin, ecnmics has traditinally stressed differences in gegraphy as a ptential determinant f ecnmic develpment (Acemglu, Jhnsn and Rbinsn, 2005). Gegraphy is thught t structure the pprtunities fr material welfare experienced by ecnmic agents. This is particularly salient in agrarian scieties which are heavily dependent upn climate and gegraphy as technlgical cnstraints. Acemglu, Jhnsn and Rbinsn (2001) als suggest health as a channel thrugh which gegraphy influences ecnmic develpment. Many diseases like malaria are nly fund in certain areas f the wrld with devastating effects n ecnmic develpment. We use the lg f muntainus terrain, gegraphic latitude and the lg f air distance t the nearest prt as ur instrumental variables set I. This set f instruments was used t derive the results described abve. It

14 13 is designed t be a first apprach t dealing with endgeneity within the cntext f this mdel. While these instruments are arguably crrelated with GDP per capita, the crrelatin might be weak. Furthermre, if we are prepared t assume that gegraphy determines the ecnmic chice set available t an individual it is easy t extraplate that it als shapes the plitical landscape by influencing plitical preferences. Thus, gegraphy might nt prvide us with adequate instruments after all Trade-Weighted Wrld Incme Instrument Acemglu et. al. (2008) use tw different instruments fr incme in their linear specificatin. The first instrument crrespnds t the savings rate in the previus five-year perid. While we agree that it is difficult t find a priri reasns why the savings rate wuld affect demcracy, it is nevertheless cnceivable that the tw variables are crrelated, especially in develping cuntries. Hence we nly use the secnd instrument, the trade-weighted wrld incme. Let ω i,j dente the trade share between cuntry i and j in the GDP f cuntry i between Then we can write the incme f cuntry i at time t 1 as, N (4.5) I i,t 1 = ζ ω i,j I j,t 1 + ǫ i,t 1 j=1,j i where incme is measured as lg f ttal incme. Acemglu et. al. (2008) suggest the use f the weighted sum f wrld incme fr each cuntry, Îi,t 1 as an instrument. Ntice that the weights are nt estimated but crrespnd t the actual trade weights. This instrument may be prblematic if incme in cuntry j, I j,t 1, is crrelated with demcracy in cuntry j which itself is then crrelated t demcracy in cuntry i. Furthermre, the trade weights, ω i,j may be crrelated with the relative demcracy scres f cuntries i and j. We knw that mre demcratic cuntries tend t be mre pen t trade. Furthermre, there may be plitical ecnmy reasns why cuntries prefer t trade with cuntries which have similar plitical regimes. In this sense it might nt be very surprising that Iran and Cuba have preferential trade agreements in place Glbal Ecnmic Factrs The wrld incme instrument described abve has an appealing interpretatin since it is designed t capture the intuitin that business cycles are t sme extent crrelated with events in wrld markets. Trade reflects nly ne aspect f this internatinal dimensin. Recently, Harding (2008) argued that the stchastic dimensin f an ecnmy is ptentially rather large and thus numerus glbal factrs that have a substantial impact n a given ecnmy culd be identified. A statistical factr mdel can be emplyed t recver a set f rthgnal factrs that can act as internatinal surces f dmestic ecnmic fluctuatins (Kse et. al., 2003). These glbal factrs drive, t sme extent, the dmestic business cycle independently f the plitical regime f a cuntry.

15 14 Ecnmetrically, we can write the fllwing linear factr mdel fr incme: (4.6) I t 1 = ΛF t 1 + U t 1, where I t 1 is the bserved N dimensinal vectr f lg GDP, F t 1 is a p-dimensinal vectr f glbal factrs and U t 1 is a vectr f idisyncratic errrs. The cefficient matrix Λ is a matrix f individual specific weights (factr ladings). Since nly lg GDP is bserved we need t use a statistical prcedure such as Principal Cmpnents Analysis (PCA) applied t the cvariance matrix Σ = (1/T)I t 1 I t 1 t recver the latent factrs ˆF t 1. By cnstructin, this methd separates the cmmnalities F t 1 frm the idisyncratic shcks U t 1. In rder t further exclude the pssibility that the plitical regime affects the glbal factrs thrugh its effect n incme we cnstruct different values f the instruments fr each cuntry by excluding the cuntry frm the analysis. Thus, the instruments fr cuntry j crrespnd t the glbal factrs estimated frm the matrix f GDP measures fr all the cuntries in the wrld except cuntry j. 7 In many financial applicatins it is f interest t knw the exact number f factrs (Bai and Ng, 2002; Harding, 2008; Stck and Watsn, 2002). This issue is substantially cmplicated by the fact that fr persistent time series such as GDP, the latent factrs ften have a dynamic structure. If this fact is nt accunted fr a plain applicatin f PCA will recver bth the factrs and their lags under certain identificatin criteria n their strength relative t the variance f the nise (Harding, 2007). In the present case, we can ignre this debate since we nly emply the estimated factrs as instruments. The estimated factrs are nt directly interpretable since they crrespnd t cmbinatins f many different ecnmic fundamentals perating at the glbal level. Nevertheless, they are valid instruments and can be emplyed in the instrumental variable specificatin f ur mdel. Basic statistics f the instruments are presented in Table 3, in the nline appendix. While it is nt necessary nr feasible t interpret the prpsed instruments in a cncrete ecnmic setting, it is interesting t nte that the chsen principal cmpnents have similar statistical prperties acrss wrld regins. The first factr appears t be mre imprtant fr Western demcracies, while the secnd factr fr Sub-saharan African cuntries. Similarly the furth factr appears less imprtant fr Eastern Eurpe and the Sviet Unin. This is cnsistent with the ntin that we are capturing glbal ecnmic factrs acting as surces fr the transmissin f internatinal business cycles while still expecting reginal variatin in their impact Rbustness t Instrument Chice In Table 3 and Figure 3 we present the estimatin results fr the baseline pled mdel after we instrument fr incme with ne f ur three sets f instruments. The left panels in Figure 3 cmpare the estimated 7 We have als experimented with excluding all cuntries in the gegraphic regin t which j belngs in the cnstructin f the instrument fr j but have btained very similar results.

16 15 quantile effects f incme n demcracy between the quantile regressin (QR) estimatr crrespnding t the pled mdel and the instrumental variable (IV S1-3) estimatrs crrespnding t the instrumental variable quantile regressin estimatrs using the three sets f instruments. In Table 3 we reprt results fr = {0.1, 0.25, 0.5, 0.75, 0.9}. Several f the estimated cefficients at the 0.9 quantile, hwever, are zer, which makes us dubt that the instrumental variable estimatr wrked fr this quantile. Fr cmputatinal rbustness, we restrict ur attentin in Figure 3 t twelve quantiles between 0.2 and 0.8. We believe that sme f the ther estimated nil effects can als be explained as cmputatinal limitatins. Hwever, results appear fairly rbust, at least frm a cmputatinal pint f view between the 0.2 and 0.8 quantiles. Fr bth measures f demcracy, estimatin using the first set f instruments, crrespnding t the gegraphic variables, nly amplifies the inverted U-shaped relatinship as described in the previus sectin. The secnd set, crrespnding t the trade weighted wrld incme instrument, nly replicates these results fr the lwer half f the distributin. The estimated cefficients fr the high quartiles are higher than at the median. Fr the Plity measure the estimated cefficient increases frm t while fr the Freedm Huse measure it increases frm t at the = 0.75 quantile. If we nw emply ur last set f prpsed instruments, we find that the inverted U-shape relatinship is preserved fr the Plity measure but nt fr the Freedm Huse measure. The estimates fr the Plity measure are slightly lwer than thse fr the pled quantile mdel and almst 50% smaller than thse btained using the first set f gegraphic instruments. The crrespnding relatinship fr the Freedm Huse measure, hwever, estimated a very high impact f incme at high quantiles f demcracy. Overall, it predicts an increasing relatinship between incme and demcracy ver the quantiles. While we have btained mixed results under the different instrumentatin strategies, it appears that mst specificatins preserve the inverse U-shaped relatinship between incme and demcracy at different quantiles f demcracy. The different specificatins appear t disagree mstly n the effect f incme in the high quantiles. Hwever all specificatins, appear t cnfirm a psitive effect f incme n demcracy in the middle range f the demcracy distributin. All but ne specificatin estimate a lwer effect f incme n demcracy in the lw quantiles cmpared t the median. Thus, after implementing three different strategies addressing the ptential endgeneity f incme, we still find higher incme t be a mre imprtant frce fr demcratizatin in hybrid regimes clse t the median f the demcracy distributin and t have almst n effect in nn-demcratic regimes. 5. Panel Data We have attempted t estimate the structural effect f incme n demcracy using a number f instrumental variables strategies. Acemglu et. al. (2008) shw, in the cntext f linear regressin, that this might be insufficient in the presence f lng run unbserved institutinal factrs which cnditin the equilibrium paths

17 16 f bth ecnmic and plitical develpment. This challenges the ntin that a small set f cntemprary explanatry variables such as incme r ppulatin can d a gd jb at explaining the distributin f demcracy arund the wrld. As we anticipated in Sectin 3.1.1, if we augment ur ecnmetric specificatin with cuntry specific effects, we are ging t find that the inverted U-shaped relatinship breaks dwn. In this sectin we will explre this effect in greater detail. First hwever, let us prvide sme preliminary evidence n the persistence f the bimdal distributin f incme even after cnditining n incme and schling. T this effect, we cnstruct the (kernel smthed) cnditinal density f demcracy fr each f the tw measures f demcracy. The tw cnditining variables are incme and schling. In Figure 4 we cmpare the uncnditinal and cnditinal distributins fr the tw measures f demcracy and fr three partitins f the cnditining variables, lw, median and high. These partitins are chsen based n the quantiles f the respective variables. Thus, when we cmpute f(d Lw I), we cmpute the distributin f demcracy cnditinal n incme being belw the 25th percentile. Similarly, high crrespnds t the cnditining variable being abve the 75th percentile with the remaining mass allcated t the median. As can be seen frm Figure 4, in almst all cases, the cnditinal distributin f demcracy retains its bimdal shape after cnditining n incme and schling. Incme and schling are nly partially able t explain the bserved shape. Cnsider fr example the distributin f the Plity measure in the first rw f Figure 4. Ntice the change in the distributin f demcracy as we first cnditin n lw incme. The uncnditinal distributin has the bimdal shape discussed abve. After cnditining we find the frequency f cuntryyears with lw demcracy scres increasing while the frequency f cuntry-years with high demcracy scres decreasing. The bimdal shape remains, illustrating the fact that even after cnditining n lw incme we still find cuntries with bth high and lw scres f demcracy. Similarly, when we cnditin n high incme we find a higher frequency f cuntry-years with a high demcracy scre but als a substantial number with lw demcracy scres. This pattern is repeated thrughut the panels in Figure 4. This pints t the pssible existence f mre lng run influences that shape the plitical develpment f a cuntry and which is nt susceptible t the cntempraneus effects f incme and schling but itself may determine these. As previusly hinted, we will attempt t use panel data methds t cntrl fr these frces Lcatin Shifts The simplest pssible quantile mdel which allws fr fixed effects is given by the fllwing equatin fr the -th cnditinal quantile functins f demcracy fr cuntry i at time t, (5.1) Q Di,t ( I i,t 1, x i,t, µ i ) = γ()i i,t 1 + x i,tβ() + µ i.

18 17 This extends the standard pled mdel discussed abve by allwing fr an individual specific effect µ i, which des nt vary acrss quantiles. These effects shuld be simply interpreted as cuntry-specific intercepts that shift the cnditinal quantiles functins by µ at each quantile. We call this mdel the lcatin-shift quantile regressin mdel (labeled FEQR (LS) in the tables and graphs). This mdel can be estimated fr J quantiles simultaneusly by slving, J N T (5.2) arg min ω j ρ j (D i,t γ( j )I i,t 1 x i,tβ( j ) µ i ), j=1 i=1 t=1 using the methd described in Kenker (2004). The weights ω j cntrl the influence f the j-th quantile n the estimatin f the quantile effects. In the present study, we will emply equal weights 1/J. If we nw turn ur attentin t Figure 3, we can evaluate the plts f the quantile effect f incme n demcracy at different quantiles after we estimate individual specific effects. (The interested reader can see the nline appendix fr a similar analysis based n schling). The figure reveals that nce we add cuntry effects the inverted U-shaped relatinship disappears. This result is cnsistent with the mean regressin results f Acemglu et. al. (2008), wh als find that nce cuntry effects are added t the specificatin the relatinship between incme and demcracy disappears. Within the cntext f quantile regressin hwever, we can take the analysis a step further and investigate the nature f the cuntry effects. If we assciate different plitical utcmes with different sets f lng run institutins, we can ask the questin whether these institutins have the same impact at different quantiles f the demcracy distributins Distributinal Shifts In large T panel data it is pssible t estimate a different value f the individual effect fr each quantile f the cnditinal distributin f the respnse. This is a nvel pprtunity which allws us t evaluate the rle f the cuntry effect, and by implicatin the lng run drivers f demcracy which it prxies fr, as they vary ver the distributin f demcracy. T ur knwledge this is the first time that distributinal cuntry effects have been emplyed in empirical wrk. T intrduce the cncept, let us first estimate a quantile grup effect befre prceeding with the estimatin f cuntry specific effects. The mdel f interest fr the -th cnditinal quantile functin f demcracy fr cuntry i at time t in the presence f grup effects is, (5.3) Q Di,g,t ( I i,g,t 1, x i,g,t, µ i,g ) = γ()i i,g,t 1 + x i,g,tβ() + µ i,g (). We can allcate each cuntry t a grup g based n the quartiles f the distributin f the mean value f a cuntry s variable f interest. Thus, fr example we can divide the cuntries int fur grups based n average schling, lw, middle-lw, middle-high, and high. A similar gruping can be dne fr incme. We als cnsider tw variables meant t capture the presence f lng run institutins based n the

19 18 wrk f Acemglu et. al. (2008). These crrespnd t estimated settler mrtality and ppulatin density in In Tables 5 and 6, in the nline appendix, we present the cmpsitin f each f the fur grups fr the fur variables f interest fr all cuntries fr which data was available. In Figure 5, we present the plts f the estimated quantile grup effects fr the first three grups using the high grup as reference pint. In each graph, the cntinuus dtted line shws the pint estimates, and the shaded regin represents a 95% cnfidence interval fr the pint estimates. The estimate grup effect fr the lw schling grup is negative but has a psitive slpe ver the quantiles f the demcracy distributin. The grup effect fr the middle-lw grup is als negative but clser t zer than the effect fr the lw grup. Bth grup effects are statistically significant at all quantiles. The estimated grup effects fr the middle-high schling grup are very clse t zer and statistically insignificant. This shws that the presence f individual effects is much mre prnunced fr lw schling cuntries and that the effect f these lng run factrs diminishes fr mre demcratic cuntries. This shws that there is substantial hetergeneity impacting cuntry specific effects n demcracy. If we nw grup the cuntries by incme we find a similar pattern t the ne where we grup the cuntries by schling. The effect is negative and significant nly fr lw incme cuntries in the lwer quantiles f the demcracy distributin. Additinally we find psitive significant quantile grup effects fr cuntries with lw and middle-lw settler mrtality but n significant grup effects fr cuntries with different ppulatin densities in This analysis strngly suggests that cuntry specific effects are nt likely t be unifrmly imprtant fr all cuntries in the sample. Mrever their significance diminishes as cuntries becme mre demcratic. The impact f cuntry hetergeneity is likely t be very mixed. The impact f lng run factrs is likely t be strnger in cuntries with bth a challenging past and unfrtunate present ecnmic and histrical circumstances, but that nce a cuntry vercmes the effect f bad initial cnditins these lng run factrs will diminish in imprtance. In rder t explre this pint further, we can nw prceed t estimate individual quantile effects fr all cuntries. The -th cnditinal quantile functin f demcracy fr cuntry i at time t in the presence f individual effects is, (5.4) Q Di,t ( I i,t 1, x i,t, µ i ) = γ()i i,t 1 + x i,t β() + µ i(). We call this mdel the distributinal-shift cuntry effects quantile regressin mdel (labeled FEQR (DS) in the figures). Ntice that we nw estimate a series f individual effects, ne fr each quantile, fr every cuntry. The prcedure requires the estimatin f N cuntry specific effects and thus is nly feasible fr large T. Fr identificatin purpses, we estimate a mdel withut an intercept term. This mdel can als easily be extended t the instrumental variable case fr each f the three sets f instruments emplyed in this paper (labelled IVFE-S1 thrugh IVFE-S3).