Abstract
I investigate the effect of political representation on local economic development, as measured by nighttime light intensity (NTLI), in Turkey between 1996 and 2013 (i.e., between legislative term 20 and 24). Parliamentary seats are apportioned by a rule that generates randomness in the extent of provincial representation in the Turkish Parliament. By exploiting that exogenous variation, I estimate the impact of one additional Member of Parliament (MP) representing a province on that province’s economic growth. Specifically, I show that an extra MP increases the NTLI of her province by 1% in a given year, which corresponds to an annual increase of 0.095% in real GDP. The increase likely is driven by MPs who are members of the government party. By investigating the mechanisms, I find that additional provincial representation increases the number of discussions of that particular province in public parliamentary meetings, as well as the funds allocated to that province. Taken together, my results suggest that some of Turkey’s regional economic growth is associated with legislative representation.
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Notes
Early Athens, the Paris Commune, and some US states historically have adopted direct democracy.
Their results, whose sample period is from 1972 to 1990, are sensitive to the time period studied; the positive effect of more effective representation on federal spending seems to hinge on events that happened between 1972 and 1982 (Matthews et al. 2011).
The main reason could be the difficulty of applying a clear and valid identification strategy. It is possible that a district’s political representation is correlated with unobserved determinants of its economic growth. In general, more representation often is associated with larger population, which, in turn, might be associated with such unobservables. Different regions with different populations could have different technological bases, different discount rates, and different incentives for human capital formation and knowledge expansion, all of which are difficult to quantify, but influence a region’s economic fortunes (Simon 1986; Becker et al. 1999). It also is challenging to distinguish empirically between the effects of political representation from the effects of either population levels or changes in them (Elis et al. 2009). Although Elis et al. (2009) utilize the method of equal population proportions in the US House to capture the causal effect of representation on the distribution of federal outlays, they rely on a relatively small sample of 53 observations.
Factors that influence a district’s economic development directly include economic institutions, capital, knowledge, technology, population, natural resources, geography, political stability, distributive policies and governmental size (Lewis 2003; Acemoglu et al. 2005; Rodrik 2012, 2014, 2018), democracy (Barro 1996; Tavares and Wacziarg 2001; Acemoglu et al. 2019), and political institutions (Przeworski and Limongi 1993).
Term 24 actually spans from 2011 to 2015, but the nighttime light data are not available after 2013. I use a province’s average NTLI per term as the proxy of provincial economic development, thus the estimated effect could be a lower bound.
In term 20, Turkey had 79 provinces because Duzce belonged to Bolu and Osmaniye belonged to Adana; in term 21, it had 80 provinces because Duzce still belonged to Bolu while Osmaniye was separated from Adana. Since term 22, Turkey has been composed of 81 provinces.
The number of MPs representing a province actually consists of three parts. Hereinafter, I focus on the two parts coming from the second and third step of the apportionment rule. Because in the first step each province gets at least one seat, in regressions whether or not that step is included will result only in a difference in the constant term.
The total population of Turkey was approximately 60 million in 1995, and it went up to approximately 72 million in 2010. That is, each MP represented about 60 million/469 = 127,932 individuals in 1995 and 72 million/469 = 135,518 individuals in 2010.
A constitutional referendum in 2007 changed the timing of subsequent elections to every four years.
In fact, the unanticipated changes in the election dates did not happen only in my sample period. Throughout Turkish history, only a handful elections were held when they were scheduled. That feature primarily is explained by the country’s political instability, possibly caused by multi-party elections and a number of interventions of the military through coups.
The Turkish Statistical Institute (TSI) stopped producing province-level GDP statistics in 2001 and restarted it in 2004. Besides the missing 2 years of GDP information (2002 and 2003), the two series are not comparable, as the TSI started using a different method for computing GDP in 2004.
The original index values range from 0 to 63, which are multiplied by 1000 in my sample.
The average \(NTLI\) is 3.372; therefore, the percentage increase is computed as (0.135/3.372) * 100, which is an increase of 4% in a parliamentary term or, an increase of 1% per year.
I also have checked whether the results are sensitive to my selection of a bandwidth equal to 0.169. I re-estimate Eq. (4) using bandwidths such as 0.1, 0.2, 0.25, 0.3, and so on. The results remain virtually unchanged.
In Turkey, government spending is first drawn up by the governing party without any public information; the draft is then discussed in parliamentary meetings for the 550 MPs to vote for or against it. Because the governing party has the largest representation at the national level, such a draft is very likely to pass, an outcome that aligns with the findings of Ansolabehere and Snyder (2006). In Turkey, the governing party has changed from time to time. It was RP (the Welfare Party) in term 20, DSP (the Democratic Left Party) in term 21, and AKP (the Justice and Development Party) in terms 22, 23 and 24.
\(An\;additional\;seat\;to\;gov._{pt}\) and \(An\;additional\;seat\;to\;oppo._{pt}\) represent the extra seats assigned to the governing party, and to the opposition party in Province \(p\) for Term \(t,\) respectively; they add up to \(An\;additional\;seat_{pt}\). \(Seats\;prop.\;to\;pop.\;won\;by\;gov._{pt}\) stands for the number of seats allocated to the governing party that are proportional to population in Province \(p\) for Term \(t\); \(Seats\;prop.\;to\;pop.\;won\;by\;oppo._{pt}\) is the difference between \(Seats\;prop.\;to\;pop._{pt}\) and \(Seats\;prop.\;to \;pop.\;won\;by \;gov._{pt}\).
The Turkish Parliament organizes parliamentary sittings according to the Rule of Procedure. MPs can speak if either their names are on the list of speakers or they are granted permission by the Speaker (Head). Once MPs are given the floor, they express their opinions about the subject being discussed. Those subjects include budget, education, culture, youth, development, tourism, and environment, and the like.
The content is translated into English. The original language is Turkish. It is cited from the speech given by MP Ugur Bayraktutan, representing Artvin, on Nov. 13, 2012.
The content of every parliamentary session is recorded in the Journal of Minutes of Turkiye Buyuk Millet Meclisi (TBMM). The speeches all are available on the official website of TBMM, where each word spoken by every MP is written down. For instance, in the speech above by MP Ugur Bayraktutan, the number of times that Artvin Province is mentioned is counted as 1.
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Acknowledgements
I thank Duha Altindag for his valuable suggestions and advices, Kang Sun for his technical support, Nicolas Ziebarth, Hyeongwoo Kim, Chris Vickers, Aditi Sengupta, and Gilad Sorek for their professional help. I thank Chris Elvidge for his explanation of the nighttime light intensity data.
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Appendix
Appendix
1.1 The D’Hondt method
The Turkish Parliament applies the party list (closed list) system. Given the predetermined number of seats for each province (N), each party submits a list of candidates ordered from 1 to N. The quotient is calculated for every candidate, which is equal to the vote share obtained by the party divided by the ranking of the specific candidate. For example, the quotient of the top-ranked candidate is exactly the vote share of the party, the second-ranked candidate has a quotient equal to half of the vote share, and the third-ranked candidate has a quotient equal to one-third of the vote share, and so on. As a result, higher-ranked candidates, such as the candidates who rank first, are elected before the lower-ranked candidates, such as those Nth ranked, within the same party in a province. Finally, all quotients are ordered from the largest to smallest, and the top N candidates with the top N quotients will be sent to the parliament and become MPs in the subsequent legislative term.
Discontinuity of the number of seats based on province’s decimal (term 20)
Table 10 provides a numerical example to describe how the D’Hondt method is used in practice. In that example, five parties, V to Z, compete for six contestable seats from a given province. Each party has a ticket on which six candidates are ordered and for each candidate, the quotient is calculated. Column (2) of Panel A shows the vote share distribution of the five parties, followed by the quotients of all candidates for each party. According to the values of the quotients, the first-ranked candidates of parties W, X, Y and Z, together with the second-ranked candidates from parties Y and Z, win seats. Now, suppose that 2% of the vote share transfers from Party Y to Party V, with everything else remaining fixed, as reflected in Panel B. Following the same procedure as before, it is the first-ranked candidates of the five parties, together with the second-ranked candidate from Party Z, who win seats. A small change in the vote share among parties consequently could lead to different candidates being elected.
1.2 Nighttime light intensity (NTLI) and its relationship with GDP
I use the NTLI to measure a region’s economic development. That is because, in Turkey, no consistent measurement of GDP by province is available during my sample period (1995–2013). An extensive literature has shown that NTLI is a valid proxy for regional economic development. In fact, a variety of existing papers have used NTLI and GDP interchangeably.
I estimate the correlation between NTLI and GDP using my subsamples based on the equation specified below, which follows Henderson et al. (2012):
where \(Real\;GDP_{pt}\) and \(NTLI_{pt}\) indicate the real GDP and NTLI of Province \(p\) in parliamentary Term \(t\), respectively. I also include province fixed effects (\(\mu_{p}\)) and term dummies (\(\tau_{t}\)) in the regression. The results of the two subsamples are reported in Table 11. The estimated \(\gamma\) s are positive and statistically significant. On average, the estimators show that a 1% increase in the NTLI of a province is associated with an approximately 0.095% increase in its real GDP. The results verify that NTLI is a good measurement of regional economic development in my setting (Tables 12, 13).
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Zhang, J. More political representation, more economic development? Evidence from Turkey. Public Choice 187, 275–299 (2021). https://doi.org/10.1007/s11127-019-00773-6
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DOI: https://doi.org/10.1007/s11127-019-00773-6