Does Consensus Democracy Improve Economic Outcomes? · Democracy (2012), Lijphart recommends the...

Does Consensus Democracy Improve Economic Outcomes?

Anna Colley

Worcester College, Oxford University

March 2018

Introduction

Of unparalleled importance to the framers of democratic constitutions is the relationship

obtaining between the nature of the institutions adopted and performance. In Patterns of

Democracy (2012), Lijphart recommends the consensus model of democracy over the

majoritarian model in virtue of delivering superior economic outcomes. Yet, in this essay, I

will reject Lijphart’s conclusion that consensus democracy improves economic outcomes by

arguing that the causal relationship he identifies is spurious. Firstly, I will address Lijphart’s

ad hoc identification of outliers and confounding variables. Once all outliers are excluded and

economic openness controlled for, the statistical significance he finds is undermined.

Subsequently, I will question the appropriateness of his inclusion of interest group

corporatism as a component of consensus democracy. And, lastly, I will suggest that

Lijphart’s case selection is to his advantage, for no robust relationship between consensus

democracy and economic outcomes is established amongst a sample of ten younger

democracies.

Definitions

Lijphart’s typology of democracies is simple: majoritarian democracies are governed by

majority rule, whereas consensus democracies seek to maximise agreement. Following

Lijphart, I will focus exclusively on the executives-parties dimension of his majoritarian-

consensus dichotomy1. To operationalise ‘economic outcomes’, I will ignore the growth rate

of Gross Domestic Product on the basis that Lijphart’s empirical analysis found no statistical

significance between this and the executives-parties dimension and will look solely at

inflation, as measured by the Consumer Price Index, and unemployment.

Theoretical Argument

The theoretical basis for Lijphart’s claim is far from implausible. Consensus democracies

tend to contain a greater number of veto players than majoritarian democracies; hence, their

economic policies are likely to find greater stability and broader support (Lijphart, 2012;

Tsebelis, 2002). Both of these attributes go some way to justify ascribing superior economic

outcomes to consensus democracies.

1 Lijphart’s executives-parties dimension is comprised of five variables. A consensus democracy has a dominant

legislative, a multiparty system, a proportional electoral system, corporatist interest groups, and unconcentrated

executive.

In the first place, it is not unreasonable to suppose that consensus democracies will

outperform majoritarian democracies in key indicators of economic performance in virtue of

having more stable economic policies. Sharp reversals of economic policy undeniably have

damaging repercussions on the rates of inflation and unemployment; and such reversals are

not uncommon amongst majoritarian democracies, where the two dominant parties take turns

as government and opposition. These reversals, or rather potential reversals, translate into

uncertainty as legislative elections draw near, too. And as Canes-Wrone and Ponce de Leon

note, uncertainty surrounding economic policy delays investment, particularly in capital and

other sunk costs (Canes-Wrone & Ponce de Leon, 2014). This is then associated both with a

reduction in the creation of new employment opportunities and with a reduction in the growth

of output that generally tempers price increases. Yet this is not the only way in which the

detrimental effect had on economic outcomes by the volatility of economic policy within

majoritarian democracies is exacerbated. Policymakers face a greater temptation to use the

fiscal tools at their disposal to stimulate a short term economic boom such that they stand a

higher chance of re-election, too. Myopically, suboptimal short term economic policies are

thus favoured (Aisen & Veiga, 2011).

In the second place, there is certainly some force behind Lijphart’s argument that the

decisions concerning economic policy reached by the governments of consensus democracies

are likely to be more successful than those of their majoritarian counterparts in virtue of

representing a greater section of society (Lijphart, 2012).

But there are strong counterarguments to consider.

The many veto players within consensus democracies indeed generate a demand for broad

agreement; but they do not ensure that this is supplied (Anderson, 2001). It is therefore quite

possible for consensus democracy to be altogether rather undeserving of its name. It is, after

all, obvious that the more veto players there are, the more difficult it becomes to reach an

agreement satisfactory to all. Less obvious, but no less important for economic outcomes, is

the decrease in the relative size of each political grouping. This increases their motive to

pursue particularist interests. Hence, consensus democracy need not necessary entail more

effective representation, nor more durable and acceptable economic policies.

Beer’s maxim ‘representative government must not only represent, it must also govern’

captures the traditional hypothesis that majoritarian democracies deliver more effective

policies than consensus democracies (Beer, 1998). Much can be said in favour of this

hypothesis; indeed, much literature has, with Lowell going so far as to state his ‘axiom’ that

one-party cabinets are required for effective policy (Lowell, 1896). One supportive point

meriting mention here is that majoritarian democracies can respond more quickly to

exogenous aggregate demand and supply shocks.

There are, then, strong theoretical arguments both for and against Lijphart’s claim. Whether

or not consensus democracies really do outperform majoritarian democracies in their control

of inflation and unemployment consequently becomes a purely empirical matter. Prima facie,

the statistically significant relationship Lijphart finds between these variables appears to

settle the dispute. But this can be doubted. I propose to do just this by probing his treatment

of outliers, control variables, components, and cases in turn.

Empirical Analysis

A: Lijphart’s Findings

Lijphart’s empirical analysis finds a statistically significant relationship between both

inflation and unemployment and consensus democracy. For every one percentage point

increase in the extent to which a country fits the consensus model of democracy, his

multivariate regression indicates a fall in inflation by almost one-and-a-half percent and a fall

in unemployment by nearly two percent.

B: Identifying and Excluding Outliers

However, Lijphart gives no procedural justification for identifying Israel and Uruguay as

outliers with respect to inflation and seemingly omits to consider whether any democracy’s

unemployment ought to be treated as an outlier.

As figure 1 demonstrates, in fact a third country, namely, Jamaica, has an average annual

inflation rate that should be excluded from Lijphart’s analysis; and, regarding unemployment,

Jamaica and Spain are outliers and as such should be excluded.

Figure 1: Boxplots depicting inflation and unemployment for Lijphart’s thirty-six

democracies

Table 1: Lijphart's multivariate regression

Dependent variable:

CPI 1981-2009 Unemployment 1981-2009 (1) (2)

Executive-parties dimension 1981-2009 -1.480** -1.794* (0.607) (0.929)

Logged population in thousands 2009 -0.800** -0.468 (0.356) (0.676)

HDI 2010 -22.557*** -11.290 (6.057) (15.227)

Constant 32.348*** 22.792** (6.010) (10.518)

Observations 26 20

R2 0.592 0.369

Adjusted R2 0.537 0.251

Residual Std. Error 2.952 (df = 22) 3.247 (df = 16)

F Statistic 10.659*** (df = 3; 22) 3.124* (df = 3; 16)

Note: *p<0.1; **p<0.05; ***p<0.01

Removing these outliers, the relationship between consensus democracy and unemployment

is rendered statistically insignificant. Lijphart’s claim that consensus democracy improves

economic outcomes is no longer valid; at best, he can claim that consensus democracy

improves the control of one economic outcome, inflation. And, while still meaningful, the

impact seemingly had by consensus democracy on inflation is deflated.

Table 2: Regression results having excluded outliers

Dependent variable:


Executives-parties dimension 1981-

2009 -0.943** -1.105

(0.374) (0.778)

Logged population in thousands 2009 -0.440* -0.618 (0.218) (0.546)

HDI 2010 -15.285*** -4.251 (3.736) (13.059)

Constant 22.110*** 17.414* (3.886) (9.695)

Observations 24 18

R2 0.595 0.230

Adjusted R2 0.535 0.065


F Statistic 9.808*** (df = 3;

20) 1.393 (df = 3; 14)

Note: *p<0.1; **p<0.05; ***p<0.001

C: Economic Openness

One obvious potential explanatory variable for a country’s macroeconomic performance is

its level of economic development; another is population. Both of these Lijphart

acknowledges, controlling for HDI and the natural logarithm of the population in thousands.

Lijphart does not, however, control for the possible confounding variable which is the level

of exposure a country faces to external influences. How successfully a country achieves a

low rate of unemployment and inflation depends, to some extent, on the monetary, fiscal,

trade, and social support policies implemented by others. Economic openness, then, should

be controlled for. In operationalising economic openness, I have used the World Bank’s data

concerning trade as a percentage of GDP for 1996, as the median year for this time period.

Controlling for economic openness has two important effects on the relationship between

consensus democracy and economic outcomes. Firstly, the fit of the model is improved:

58% of the variation in inflation and 8.8% of the variation in unemployment can be

explained, whereas previously the respective R-squared figures were 0.535 and 0.065.

Secondly, no statistical significance reappears for inflation and, again, while the relationship

between consensus democracy and inflation remains significant at the 5% level, it becomes

weaker.

Table 3: Regression results having excluded outliers and controlling for economic openness

Dependent variable:

CPI 1981-2009 Unemployment

1981-2009 (1) (2)

Executives-parties dimension 1981-2009 -0.803** -1.065 (0.366) (0.769)

Logged population in thousands 2009 -0.832** -0.035 (0.307) (0.737)

HDI 2010 -16.472*** -5.954 (3.629) (12.983)

Economic openness 1996 -0.029* 0.037 (0.017) (0.031)

Constant 28.771*** 10.990 (5.344) (11.060)

Observations 24 18

R2 0.650 0.302

Adjusted R2 0.577 0.088


F Statistic 8.836*** (df = 4; 19) 1.408 (df = 4; 13)

Note: *p<0.1; **p<0.05; ***p<0.001

D: Interest Group Corporatism

One or more of the features associated with consensus democracy rather than the concept

itself may be responsible for Lijphart’s findings. Indeed, just one component of the

executive-parties dimension, interest group corporatism, drives the connection Lijphart finds

between consensus democracy and improved economic outcomes (Anderson, 2001). The

mechanism for this connection is well known (Cameron, 1984). Within countries that have

corporatist interest groups, business and labour interests are brought together. This means that

the costs of pursuing particularist goals are acknowledged, such that wage and price increases

are willingly sacrificed in favour of full employment and price stability (Anderson, 2001).

But the theoretical connection between interest group corporatism and consensus democracy

is tenuous. Interest group corporatism seems to go equally well with the majoritarian model

as it does with the consensus model, for the centralisation typical of majoritarian democracies

may well be thought to extend to interest groups (Taagepera, 2003). There therefore seems to

be no persuasive reason for the inclusion of the degree of interest group corporatism within

his executives-parties dimension.

Given the conspicuous lack of a theoretical basis for including interest group corporatism as a

feature of consensus democracy, the executives-parties dimension ought to be recreated

without this.

Given also the strong correlation between the original and reformulated executives-parties

dimensions (Pearson’s product moment correlation coefficient takes a value of -0.98 with a p-

value less than 2.2e-16; see figure 2), if consensus democracy and not merely interest group

corporatism is responsible for superior economic outcomes, then the relationship between the

new executives-parties dimension and both inflation and unemployment should be

statistically significant.

But this is not the case; eliminating the degree of interest group corporatism eliminates all

statistical significance.

Figure 2: The relationship between the original and reformulated executive-parties

dimensions

Table 4: Regression results having excluded outliers and controlling for economic openness

with the new executive-parties dimension which lacks the degree of interest group pluralism

Dependent variable:


Executives-parties dimension 1981-

2009 0.753 0.764

(0.454) (0.936)

Logged population in thousands 2009 -0.819** 0.145 (0.324) (0.750)

HDI 2010 -16.880*** -9.603 (3.789) (13.138)

Economic openness 1996 -0.030 0.039 (0.018) (0.033)

Constant 29.053*** 12.140 (5.624) (11.517)

Observations 24 18

R2 0.617 0.238

Adjusted R2 0.536 0.004


F Statistic 7.651*** (df = 4; 19) 1.017 (df = 4; 13)

Note: *p<0.1; **p<0.05; ***p<0.01

E: Ten Younger Democracies

Lijphart’s prescription that constitutional engineers should favour the consensus model of

democracy to yield the best economic outcomes may be queried for another reason. Setting

aside any concerns about outliers, controls, and conceptualisation, the conclusion Lijphart

draws from his sample of democracies may not be generalisable across the wider population.

Lijphart’s case selection may be to the advantage of his hypothesis. His thirty-six

democracies represent the rather uniform experience of Latin America and southern Europe;

of his cases, just ten are outside these geographical regions and only six are presidential.

There is then a real concern that the choice of political institutions by the countries within his

sample and their economic performance depends upon a cultural factor. This makes sense of

Fortin’s (2008) inability to replicate Lijphart’s findings for nineteen Eastern European

countries, and the fact that Croissant and Schächter (2009) again fail to replicate Lijphart’s

findings, this time across nine Asian countries between the 1980s and 2005.

Neither of these studies adopt Lijphart’s definition of democracy or operationalisation of the

components of the executives-parties dimension exactly. So, to test whether the positive

relationship he finds between consensus democracy and economic outcomes within his

sample is merely a result of his selection of cases according to constructive consensual

culture, a new sample of democracies meeting his definition and operationalisation must be

taken.

Following Liphart in using Freedom House’s rating of a country as free to determine whether

it qualifies as a democracy, provided that its population exceeds a quarter of a million, a

sample of ten countries newly democratic between the years 1998 and 2015 can be drawn.

These are: Belize, Benin, Bulgaria, Cape Verde, El Salvador, Estonia, Guyana, Hungary,

Latvia, and Lithuania2.

In calculating the executives-parties index for these countries, I refrained from including a

measure of interest group corporatism, partly due to a lack of data and partly due to the lack

of a justification for doing so. I followed Lijphart in measuring the effective number of

parties according to Laakso and Taagepera’s index (Laakso and Taagepera, 1979)3. I

operationalised the concentration of power within cabinets as the percentage of minimal

winning one-party cabinets. To measure executive dominance, I stuck to Lijphart’s choice of

average cabinet duration. For electoral system disproportionality I calculated Gallagher’s

index for each legislative election within the time period and took the mean. To then collate

these four variables into a single index, I adjusted each to make the mean zero and standard

deviation one after making taking the negative of the effective number of parties4.

The components of the executive-parties index for the ten new democracies show similar

interrelations to that of Lijphart’s thirty-six. Hence, there is good reason to expect that, if

Lijphart’s sample is duly representative, then his finding will be reproduced.

2 Chile also was democratic throughout the period 1998 to 2015 and was not included in Lijphart’s analysis.

However, I was unable to follow Lijphart’s method of personally adjusting his measure of executive dominance-

average cabinet duration-for presidential systems and as such deemed it better to omit Chile from my sample. 3 This I did for each legislative election held within the years 1998 to 2015 inclusive and then found the average. 4 So that a higher value for each component indicates a more consensus system.

Figure 3: Correlation matrix for the four components of the executive-parties dimension for

the new sample of democracies

Scaled

effective

number of

parties

Scaled

percentage of

minimal winning

one-party

cabinets

Scaled index

of executive

dominance

Scaled index of

electoral

disproportionality

Scaled effective

number of parties 1 0.734 0.714 0.381

Scaled percentage of

minimal winning one-

party cabinets

0.734 1 0.906 0.322

Scaled index of

executive dominance 0.714 0.906 1 0.421

Scaled index of

electoral

disproportionality

0.381 0.322 0.421 1

Figure 4: Correlation matrix for the first four components of the executives-parties

dimension for Lijphart’s 36 democracies

Effective

number of

parties

Percentage of

minimal winning

one-party

cabinets

Index of

executive

dominance

Index of electoral

disproportionality

Effective number of

parties 1 -0.801 -0.652 -0.603

Percentage of minimal

winning one-party

cabinets

-0.801 1 0.733 0.549

Index of executive

dominance -0.652 0.733 1 0.561

Index of electoral

disproportionality -0.603 0.549 0.561 1

However, there is no significant relationship between consensus democracy and economic

outcomes: both when following his original controls and when also controlling for economic

openness.

Figure 5: Regression results for ten new democracies

Dependent variable:


Executives-parties dimension 1998-2015 0.379 0.386 (0.913) (1.192)

Logged population in thousands 2007 0.718 -1.039 (0.545) (0.711)

HDI 1998-2015 4.828 22.330*** (4.469) (5.837)

Constant -5.349 1.503 (5.745) (7.504)

Observations 10 10

R2 0.355 0.767

Adjusted R2 0.033 0.650

Residual Std. Error (df = 6) 1.547 2.020

F Statistic (df = 3; 6) 1.101 6.579**

Note: *p<0.1; **p<0.05; ***p<0.01

Table 6: Regression results for ten new democracies controlling for economic openness

Dependent variable:


Executives-parties dimension 1998-2015 0.001 0.317 (0.727) (1.336)

Logged population in thousands 2007 0.920* -1.002 (0.431) (0.793)

HDI 1998-2015 -1.736 21.132* (4.538) (8.343)

Economic openness 2007 0.039* 0.007 (0.018) (0.032)

Constant -6.529 1.288 (4.481) (8.238)

Observations 10 10

R2 0.678 0.769

Adjusted R2 0.420 0.584

Residual Std. Error (df = 5) 1.198 2.202

F Statistic (df = 4; 5) 2.627 4.165*

Note: *p<0.1; **p<0.05; ***p<0.01

Conclusion

In sum, then, there is substantial evidence against Lijphart’s contention that consensus

democracy improves economic outcomes. His empirical finding conceals both theoretical and

methodological weaknesses; in addition to inadequately dealing with outliers and controls,

his creation of the executive-parties dimension itself is misleading, and his case selection too

is not beyond suspicion. What would be welcome now to either resuscitate or decidedly put

down the notion that consensus democracy has a beneficial effect on the control of inflation

and unemployment would be further investigation of culture on the choice of political

institutions and economic performance.

Word count (excluding headings, tables, figures, footnotes, and appendices): 2,177

Appendix

A: References Used

Aisen, Ari & Veiga, Francisco Jose (2011). How Does Political Instability Affect Economic

Growth? IMF Working Paper. URL (cited 31st March 2018):

https://www.imf.org/external/pubs/ft/wp/2011/wp1112.pdf

Anderson, Liam (2001). The Implications of Institutional Design for Macroeconomic

Performance. Comparative Political Studies 34(4): 429-52, doi:

10.1177/0010414001034004004

Beer, Samuel (1998). The Roots of New Labour: Liberalism Rediscovered. Economist

Cameron, David R. (1984). Social democracy, corporatism, labour quiescence and the

representation of economic interests in advanced capitalist society. In J. H. Goldthorpe (Ed.),

Order and conflict in contemporary capitalism. Oxford, UK: Clarendon.

Canes-Wrone, Brandice & Ponce de Leon, Christian (2014). Elections, Uncertainty, and

Economic Outcomes. Working Paper. Stanford University.

Croissant, Aurel & Teresa Schächter (2009). Demokratiestrukturen in Asien – Befunde,

Determinanten und Konsequenzen. Zeitschrift für Politikwissenschaft

Fortin, Jessica (2008). Patterns of Democracy? Counterevidence from Nineteen Post-

Communist Countries. Zeitschrift für Vergleichende Politikwissenschaft, doi:

10.1007/s12286-008-0014-1

Lijphart, Arend (2012). Patterns of Democracy. New Haven: Yale University Press.

Lowell, A. Lawrence (1896). Governments and Parties in Continental Europe. Boston:

Houghton Mifflin.

Taagepera, Rein (2003). Arend Lijphart’s Dimensions of Democracy: Logical Connections

and Institutional Design. Political Studies 51(1): 1- 19, doi: 10.1111/1467-9248.00409

Tsebelis, George (2002). Veto Players: How Political Institutions Work. Princeton University

Press.

B: Background References

Borman, Nils-Christian (2010). Patterns of Democracy and Its Critics. Centre for

International and Comparative Studies. URL (cited on 31 March 2018): https://www.ethz.ch/

content/dam/ethz/special-interest/gess/cis/cis-dam/CIS_DAM_2015/WorkingPapers/Living_

Reviews_Democracy/Bormann.pdf

Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.

R package version 5.2.1. https://CRAN.R-project.org/package=stargazer

C: Code

data<-read.csv("http://andy.egge.rs/data/L.csv")

library(stargazer)

#ascertaining which countries are already excluded from Lijphart's dataset

data$country

data$cpi_1981_2009

data$unemployment_1981_2009

#the five smallest states and the three states not yet democratic in 1981 have already been

excluded (of the two inflationary ouliers Lijphart identifies, only Uruguay has been excluded)

#identifying outliers

boxplot(data$cpi_1981_2009,ylab="average annual CPI inflation for the period 1981 to

2009")

boxplot(data$unemployment_1981_2009,ylab="average annual unemployment for the period

1981 to 2009")

#Israel, Jamaica and Costa Rica are outliers with respect to CPI inflation, and Jamaica and

Spain are outliers with respect to unemployment

#excluding Israel from cpi_1981_2009 in line with Lijphart's empirical analysis

data$cpi_1981_2009[18]<-NA

#recreating Lijphart's multivariate regressions

model1<-

lm(data$cpi_1981_2009~data$exec_parties_1981_2010+log(data$pop_in_thousands_2009)+

data$hdi_2010)

https://cran.r-project.org/package=stargazer

summary(model1)

model2<-

lm(data$unemployment_1981_2009~data$exec_parties_1981_2010+log(data$pop_in_thousa

nds_2009)+data$hdi_2010)

summary(model2)

#creating a multivariate regression table

stargazer(model1,model2,type="html",out="lijphart.doc",title = "Lijphart's multivariate

regression",dep.var.labels = c("CPI 1981-2009","Unemployment 1981-

2009"),covariate.labels = c("Executive-parties dimension 1981-2009","Logged population in

thousands 2009","HDI 2010"))

#excluding additional outliers identified

data$cpi_1981_2009[9]<-NA

data$cpi_1981_2009[20]<-NA

data$unemployment_1981_2009[20]<-NA

data$unemployment_1981_2009[30]<-NA

#re-running the regressions without outliers

model3<-

lm(data$cpi_1981_2009~data$exec_parties_1981_2010+log(data$pop_in_thousands_2009)+

data$hdi_2010)

summary(model3)

model4<-

lm(data$unemployment_1981_2009~data$exec_parties_1981_2010+log(data$pop_in_thousa

nds_2009)+data$hdi_2010)

summary(model4)

#CPi remains significant but unemployment does not

#creating a regression table

stargazer(model3,model4,type = "html",out = "outliers.doc",title = "Regression results having

excluded outliers",dep.var.labels = c("CPI 1981-2009","Unemployment 1981-

2009"),covariate.labels = c("Executives-parties dimension 1981-2009","Logged population in

thousands 2009","HDI 2010"))

#creating a new control variable, economic openness

economic_openness<-

c(12.506,38.172,70.05,105.857,91.548,96.775,90.956,70.3,84.492,68.471,65.737,43.937,44.9

97,37.496,70.378,22.167,138.704,61.286,42.983,99.068,18.525,53.404,190.432,237.57,127.8

58,109.129,71.122,55.116,60.208,46.328,67.489,79.67,86.896,51.305,39.528,22.611)

data1<-cbind(data,economic_openness)

#regressing now controling for economic openness

model5<-

lm(data1$cpi_1981_2009~data1$exec_parties_1981_2010+log(data1$pop_in_thousands_200

9)+data1$hdi_2010+data1$economic_openness)

summary(model5)

model6<-

lm(data1$unemployment_1981_2009~data1$exec_parties_1981_2010+log(data1$pop_in_th

ousands_2009)+data1$hdi_2010+data1$economic_openness)

summary(model6)

#CPI still significant, but smaller coefficient and larger R-squared

#creating a regression table

stargazer(model5,model6,type = "html",out = "econopen.doc",title = "Regression results

having excluded outliers and controlling for economic openness",dep.var.labels = c("CPI

1981-2009","Unemployment 1981-2009"),covariate.labels = c("Executives-parties dimension

1981-2009","Logged population in thousands 2009","HDI 2010","Economic openness

1996"))

#creating a new executives-parties dimension excluding the degree of interest group

pluralism

parties<-scale(-data$eff_num_parl_parties_1981_2010)

cabinets<-scale(data$pct_minimal_winning_one_party_cabinet_1981_2010)

exec<-scale(data$index_of_exec_dominance_1981_2010)

disp<-scale(data$index_of_disproportionality_1981_2010)

ep<-(parties+cabinets+exec+disp)/4

#checking the new executives-parties dimension is relevantly similar to the original

cor.test(ep,data$exec_parties_1981_2010)

plot(ep,data$exec_parties_1981_2010,xlab = "Executive-parties dimension without degree of

interest group pluralism 1981-2009",ylab = "Executives-parties dimension 1981-2009")

abline(lm(data$exec_parties_1981_2010~ep))

#regressing CPI and unemployment against the executive-parties dimension without degree

of interest group pluralism

model7<-

lm(data1$cpi_1981_2009~ep+log(data1$pop_in_thousands_2009)+data1$hdi_2010+data1$e

conomic_openness)

summary(model7)

model8<-

lm(data1$unemployment_1981_2009~ep+log(data1$pop_in_thousands_2009)+data1$hdi_20

10+data1$economic_openness)

summary(model8)

#displaying this via a regression table

stargazer(model7,model8,type = "html",out = "ep.doc",title = "Regression results having

excluded outliers and controlling for economic openness with the new executive-parties

dimension which lacks the degree of interest group pluralism",dep.var.labels = c("CPI 1981-

2009","Unemployment 1981-2009"),covariate.labels = c("Executives-parties dimension

1981-2009","Logged population in thousands 2009","HDI 2010","Economic openness

1996"))

#looking at countries democratic from at least 1998 to today

#processing data

parties1<-c(-1.63,-4.43,-3.85,-2.07,-3.10,-4.62,-2.25,-2.53,-6.02,-5.88)

sparties<-scale(parties1)

cabinets1<-c(100,0,27.8,100,0,0,100,0,0,0)

scabinets<-scale(cabinets1)

exec1<-c(8.5,4,4,10,3,4,7,5.33,4,4)

sexec<-scale(exec1)

disp1<-c(17.79,8.57,7.37,6.85,3.78,3.85,0.87,11.9,4.12,10.71)

sdisp<-scale(disp1)

epnewcountries<-(sparties+scabinets+sexec+sdisp)/4

#loading data

newdata<-read.csv("newdata.csv",header=TRUE)

data.frame(newdata)

#comparing the correlation between components of the executives-parties dimension for the

new democracies with that of Lijphart's

correlation_matrix<-

cor(newdata[,c("Effective.number.of.parties","Percentage.of.minimal.winning.one.party.cabi

nets","Index.of.executive.dominance","Index.of.electoral.disproportionality")])

corr_matrix<-

cor(data[,c("eff_num_parl_parties_1981_2010","pct_minimal_winning_one_party_cabinet_1

981_2010","index_of_exec_dominance_1981_2010","index_of_disproportionality_1981_20

10")])

#creating a correlation matrix table

stargazer(correlation_matrix,type = "html",out = "correlation.doc")

corr_matrix<-

cor(data[,c("eff_num_parl_parties_1981_2010","pct_minimal_winning_one_party_cabinet_1

981_2010","index_of_exec_dominance_1981_2010","index_of_disproportionality_1981_20

10")])

stargazer(corr_matrix,type = "html",out = "corr.doc")

#regressing CPI and unemployment against the executives-parties dimension for the new ten

democracies

model9<-

lm(newdata$CPI~newdata$executives.parties+log(newdata$population)+newdata$HDI

summary(model9)

model10<-

lm(newdata$unemployment~newdata$executives.parties+log(newdata$population)+newdata

$HDI)

summary(model10)

model11<-

lm(newdata$CPI~newdata$executives.parties+log(newdata$population)+newdata$HDI+new

data$economic.openness)

summary(model11)

model12<-

lm(newdata$unemployment~newdata$executives.parties+log(newdata$population)+newdata

$HDI+newdata$economic.openness)

summary(model12)

#creating regression tables

stargazer(model9,model10,type = "html",out = "newcountries.doc",title = "Regression results

for ten new democracies",dep.var.labels = c("CPI 1998-2015","Unemployment 1998-


thousands 2007","HDI 1998-2015")))

stargazer(model11,model12,type = "html",out = "newcountries1.doc",title = "Regression

results for ten new democracies",dep.var.labels = c("CPI 1998-2015","Unemployment 1998-


thousands 2007","HDI 1998-2015","Economic openness 2007")))

D: Additional Data

The data used to calculate each of the four components of the executive-parties dimension for

the ten new democracies was sourced from a combination of Wikipedia, African election

database, caribbeanelections.com, and Knoema.

These were averaged across all legislative elections within the time period, as per Lijphart’s

methodology.5

All data concerning inflation, unemployment, population and economic openness comes from

the world bank. The United Nations development programme was used to find the Human

Development Indices.

Table 1: Components of the Executive-Parties Dimension for Ten Young Democracies

Country

Effective

number of

parties

Percentage of one-

party minimal

winning cabinets

Cabinet

Duration

Gallagher’s index of

electoral

disproportionality

Executive-

parties index

Belize 1.63 100 8.50 17.79 1.523

Benin 4.4 0 4 8.57 5.980

Bulgaria 3.85 27.8 4 7.37 12.500

Cape

Verde 2.07 100 10 6.85 0.840

El

Salvador 3.10 0 3 3.78 155.200

Estonia 4.62 0 4 3.85 10,055.780

Guyana 2.25 100 7 0.87 1.276

Hungary 2.53 0 5.33 11.9 1.420

Latvia 6.02 0 4 4.12 1.981

Lithuania 5.88 0 4 10.71 2.070

5 Belize held legislative elections in 1998, 2003, 2008, 2012, and 2015. Benin’s legislative elections took place

in 1999, 2003, 2007, and 2011. Bulgaria staged legislative elections in 2001, 2005, 2009, and 2014. Cape

Verde’s occurred in 2001, 2006, and 2011. El Salvador held legislative elections in 2000, 2003, 2006, 2009,

2012, and 2015. Estonia held legislative elections in 1999, 2003, 2007, 2011, and 2015. Guyana’s were in 2001,

2006, 2011, and 2015. Hungary’s took place in 1998, 2002, 2006, 2011, and 2014. Latvia’s occurred in 1998,

2002, 2006, 2010, 2011, 2014. Lithuania’s legislative elections were in 2000, 2004, 2008, and 2012.

Table 2: Inflation, unemployment, level of development, population, and economic openness

for ten young democracies

Country

CPI,

average

1998-2015

Unemployment,

average 1998-2015

HDI,

average

1998-2015

Population in

thousands,

2007

Economic

openness,

average 1998-

2015

Belize 1.58 11.2 0.70 298,407 14.6

Benin 2.82 1.02 0.46 8,454,791 57.6

Bulgaria 5.87 11.8 0.77 8,312,068 103.4

Cape

Verde 2.18 9.2 0.63 486,438 96.9

El

Salvador 2.64 6.8 0.67 6,038,475 69.2

Estonia 3.82 9.9 0.84 1,340,680 142.3

Guyana 5.05 11.2 0.63 747,869 155.2

Hungary 5.98 9.0 0.82 10,055,780 143.2

Latvia 4.29 12.5 0.81 2,200,325 100

Lithuania 2.49 11.8 0.83 3,231,294 119.4

Does Consensus Democracy Improve Economic Outcomes? · Democracy (2012), Lijphart recommends the...

Documents

Transcript of Does Consensus Democracy Improve Economic Outcomes? · Democracy (2012), Lijphart recommends the...