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Constitutional Political Economy

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26.08.2016 | Original Paper

Poor institutions as a comparative advantage

verfasst von: Cortney Stephen Rodet

Erschienen in: Constitutional Political Economy | Ausgabe 2/2017

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Abstract

Classic theories of comparative advantage point to factor productivity and factor abundance as determinants of specialization and trade. Likewise, geography and topography can determine trade patterns. Institutions, however, are increasingly seen as important sources of comparative advantage. A global drug prohibition regime implies that institutional quality matters more than traditional sources in the drug trade. This paper theoretically models trade patterns of illicit goods and confirms the role of institutions empirically with respect to the drug trade. In particular, illicit enterprises gain force in countries where resources are scarce, drug enforcement is uncertain, and institutions are weak in absolute terms and relative to neighboring countries. I propose several policy alternatives that emphasize economic opportunity for the poor and institutional quality that complement drug prohibition.

Vorheriger Artikel Domestic institutions and the ratification of international agreements in a panel of democracies

Nächster Artikel Erratum to: Poor institutions as a comparative advantage

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There is penal flexibility across borders regarding the possession of small quantities of prohibited substances (Roberts and Chen 2013).

http://www.unodc.org/unodc/en/treaties/index.html?ref=menuside.

That is, the paper takes prohibition as given and does not consider the implications of legalization. For economic arguments against prohibition see Miron and Zwiebel (1995). See Skaperdas (2001) for an outline of economic costs derived from organized crime.

We can assume that this is a subset of the continuum of all goods, where illicit goods make up the more complex goods when considering the journey from conception to point of sale.

Using this data rather than self-reported crime rates or trade flows, although less than ideal, avoids the problem of correlation between underreporting and unobservable country characteristics (see Soares and Naritomi (2010)).

The World Fact Book does not report data by year, nor does it indicate when a country was first considered prominent in the production or transit of illicit drugs. Therefore, the data are treated as a single cross-section based on the 2015 report.

Countries on the CIA’s list that were neither producer or transit countries were noticed for consumer demand of illicit drugs. I classify these countries, along with countries that do not appear in the Fact Book, as ‘neither’.

Nine countries in the EFW sample are producers only, 48 are transit only and 24 are both.

Estimating a Spatial Durbin Model (SDM) was considered and tried; however, tests indicate that the constructed spillover variable, as well as the other control variables, accounts for spatial dependence in the fitted logit model (Moran’s I z-score = 0.56, p value = 0.29). More importantly, the estimation method presented here allows for an intuitive presentation of the results. Any spatial dependence not controlled for leaves estimates unbiased but inconsistent, so I estimated the benefits of using the logit model outweighed the potential cost of not using the SDM.

The data and methodology are available here: http://diegopuga.org/data/rugged/.

A full description of methodology can be found here: http://www.transparency.org/cpi2014/in_detail. Likewise, the appendix includes sources and their respective summaries.

I assume a linear relationship regarding institutional quality and find a significantly negative relationship between it and the probability of being a trafficking country; however, relaxing the linear relationship assumption and splicing the variable into quartiles to allow for different slopes results in similar findings as shown in the appendix. Also, note that including control variables for global location, such as continent or subcontinent, presents identification issues because being a South American country perfectly predicts being a trafficking country.

The neighbors include Armenia (IQ = 4.25), Bulgaria (IQ = 3.07), Greece (IQ = 5.69), and Iran (IQ = 5.96). Data on Syria is not available.

The neighbors include Austria (IQ = 9.15), Czech Republic (IQ = 5.95), Hungary (IQ = 5.36), Poland (IQ = 5.69), and the Ukraine (IQ = 3.92).

One exception is Canada. This is likely attributable to the country’s ruggedness.

I differentiate here between corruption of the rule of law and corruption in politics and business, which was the measure included in the estimated model and was shown to not play a significant role in developed trade patterns.

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Titel: Poor institutions as a comparative advantage
verfasst von: Cortney Stephen Rodet
Publikationsdatum: 26.08.2016
Verlag: Springer US
Erschienen in: Constitutional Political Economy / Ausgabe 2/2017
Print ISSN: 1043-4062
Elektronische ISSN: 1572-9966
DOI: https://doi.org/10.1007/s10602-016-9224-8

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