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ABSTRACT
Political business cycles are typically linked to the manipulation of fiscal or monetary policy instruments. In a recent article, Imami, Lami and Uberti (ILU) argue that opportunistic politicians may also choose to manipulate non-fiscal/non-monetary policy instruments. Here, we extend ILU’s study using time-series data on mining-sector licensing from post-conflict Kosovo (2001–2018). We find robust evidence that is consistent with electoral opportunism in the allocation of mining permits, despite the checks-and-balance mechanisms introduced by Kosovo’s international administrators in an attempt to reduce the politicisation of licensing. That said, the cycle effect is only observed prior to scheduled, as opposed to early, elections. Disaggregating the data by licence type, in addition, we find that the observed election cycle is driven primarily by the manipulation of licences for the mining of construction materials. We argue that, in the context of post-conflict Kosovo, this is the category of licences whose strategic manipulation offers the greatest pay-off to the incumbent. The results raise some questions about the feasibility of fighting political opportunism (and, relatedly, corruption) by establishing formal check-and-balance mechanisms.
Acknowledgements
We would like to thank the participants and organisers of the conference on ‘Post-Socialism: Hybridity, Continuity and Change’ (Novi Sad, Serbia, 25–26 June 2016) for their helpful comments on a very early version of this article. Lastly, we would like to thank the Centre for Political Courage at the University of Prishtina (Kosovo) for hosting the lead author during part of the preparation of this article.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
The data and replication files are available upon request.
Notes
1. Brender and Drazen (Citation2005) find that political business and budget cycles are a phenomenon specific to recently democratised countries, regardless of income levels. Thus, it is particularly relevant to investigate PBCs in the context of a post-socialist, post-conflict country such as Kosovo.
2. In 1989, minerals (including chrome, copper and nickel) accounted for nearly 80% of total Albanian exports by value (World Bank, Citation2009, p. 17). Throughout the 1970s, metals (including lead, zinc, bauxite, magnesium) accounted for nearly 46% of Kosovo’s exports. By 1985, the share of metals in total exports had declined to 24%, however (Gashi & Pugh, Citation2015, p. 37).
3. The Agencia Kombëtare e Burimeve Natyrore (National Agency for Natural Resources).
4. Formerly, the Ministry of Energy and Industry.
5. Komisioni i Pavarur për Miniera dhe Minerale.
6. According to UNMIK, introducing a comprehensive system of licensing was crucial to ‘protecting resource assets’ (Large et al., Citation2003, p. 15). Following NATO’s 1999 intervention, leaders of the ethnic-Albanian guerrilla (KLA) had taken control of most of Kosovo’s socially-owned mining operations (Grasten & Uberti, Citation2017). Consequently, UNMIK also saw the introduction of a licensing system as an urgent response to the chaos of ‘informal’ or ‘spontaneous’ privatisation.
7. Interview with non-metallic minerals company based in Prizren, 8 April 2015. The interviewee also noted that the KPMM is otherwise fairly ‘clean’: ‘[KPMM] might delay the granting of a certain permit [perhaps to solicit a bribe payment], but eventually they give it to you’.
8. Interview with mining company based in Prishtina, 21 July 2015.
9. At the level of parliamentary politics, at least.
10. The government formed in 1996 was forced to resign following the outbreak of the 1997 civil unrest.
11. This may be especially the case if the licensing authority is formally established as an independent agency (as in Kosovo). We cannot test whether an incumbent can manipulate a non-independent agency prior to early elections since (with the exception of the 1997 elections), all post-socialist elections in Albania were scheduled elections.
12. Even though the OLS estimator is asymptotically normal (regardless of the population distribution), a linear OLS model with form might produce negative predicted values, violating a fundamental feature of count data. That said, our baseline results (Model 2, ) are qualitatively unchanged if the model is given this linear form and is estimated by OLS (with HAC standard errors). Results are available upon request.
13. The 2004 scheduled election took place during the suspension period.
14. UNMIK Regulation 2005/3 ‘On Mines and Minerals in Kosovo’.
15. Law No. 03/L-163 ‘On Mines and Minerals’, 27 August 2010. This law transferred some regulatory powers away from the mining regulator (Uberti, Citation2014a). However, since these special executive powers were never exercised in practice, the 2010 reform did not effectively jeopardise the formal independence of the KPMM. The new law was also amended again in May 2013 (Law No. 04/L-158). Since the 2013 amendments were relatively minor, however, we do not distinguish between the 2010 law and the 2013 amendments in the analysis.
16. Unlike in Albania, a substantial number of mining firms active in Kosovo (with the exception of firms owning small-scale operations) is foreign-owned. Since domestic banks provide little credit for large-scale industrial projects, firms typically rely on foreign banks for project financing. For this reason, we control for the rental cost of capital using the LIBOR rate, rather than the domestic interest rate (as ILU do). Premiums above the LIBOR rate typically take into account the risk of a mining project (which we assume to be randomly distributed) as well as the country risk (which we assume to be constant during 2001–2018). A foreign-owned firm indicated that, in their cash-flow calculations, they typically cost in an 8% interest rate, while return on capital ranges between 20 and 25% (interview with mining company based in Prishtina, 9 September 2017). The MPI and LIBOR data are taken from the IMF (https://www.imf.org/external/np/res/commod/index.aspx) and the Federal Reserve Bank of St. Louis (https://fred.stlouisfed.org), respectively.
17. Data on LIBOR and the metal price index for the last observations in the dataset (early 2018) were not yet available at the time of writing, leading to a loss of three observations when these variables are included.
18. We use GLM. The ML and GLS estimators are identical when the conditional distribution is Poisson (Cameron & Trivedi, Citation2013, p. 76).
19. This process is known as ‘true contagion’ (Cameron & Trivedi, Citation2013, p. 161).
20. The LB statistic is a weighted sum of the autocorrelation of the Pearson residuals. A higher number indicates higher residual autocorrelation.
21. Residual over-dispersion may be a consequence of unobserved heterogeneity in the data (a process known as ‘apparent contagion’). Although our data are generated by the same individual over time (the DMM and its successor agency, the KPMM), it is reasonable to assume that staff turnover at the agency may lead to different relative propensities to issue licences over time.
22. .
23. Equation (2) is re-written as: , where
and
if
, and
and
if
. Then,
is used to obtain an estimate of
.
24. Full results are available upon request.
25. Full results are available upon request.
26. The average value of the quarterly coefficients for the periods preceding scheduled elections (0.637, s.e. = 0.279, p-value = 0.023) is qualitatively consistent with the estimates obtained using annual pre-election dummies (see , model 5). Again, consistent with previous findings, the average value of the quarterly coefficients for the periods preceding early elections (−0.245, s.e. = 0.182, p-value = 0.179) is statistically indistinguishable from zero. We can reject the equality of these two averages at the 5% level (the p-value of the Wald test is 0.011).
27. Authors’ calculations based on data from Statistical Agency of Kosovo, National Accounts Statistics, 2015.
28. It is not uncommon for politicians to own quarries, often located in their electoral strongholds. The trade in construction materials in Kosovo is also partly rooted in the legacy of war economies, with business opportunities arising from post-war reconstruction and supply contracts being distributed amongst former members of the same guerrilla factions.
29. Notably, the Trepça mining and metallurgical complex in the northern city of Mitrovica.
30. This interpretation of election cycles is proposed by ILU (Citation2018).
31. =exp(1.078) = 2.94.
32. In this model the over-dispersion parameter is still large (0.404) and significantly different from zero (p-value = 0.000), even after the regressors (and the lagged dependent variable) are included. This indicates that over-dispersion does not result solely from ‘true contagion’ (i.e. serial correlation) but also from unobserved heterogeneity.