Rent-Seeking and Firm Performance: Do Institutional and Firm-Specific Characteristics Matter?

Abstract

This paper looks at the differential impact of bribery and lobbying onto the productivity of firms using data from 28 Eastern European and Central Asian economies. It is hypothesized that since the intent of lobbying is fundamentally different from that of bribery their consequences may differ. The empirical results reveal that while lobbying increases firm performance, bribery decreases it. Also, there is a need to improve institutions to mitigate some of the negative effects of bribery onto firm performance. As far as firm-level characteristics are concerned larger sized-, service sector- and exporter-firms need to be particularly shielded from bribery practices as the negative impact of bribery onto these types of firms are more pronounced. On the other hand, lobbying is found to be more successful for larger-, export oriented- and older firms, implying that such firms need to be encouraged to collaborate and forward valuable information for effective policy making.

Keywords:

• Corruption
• lobbying
• productivity
• institutional environment
• firm-specific characteristics
• developing countries

JEL CLASSIFICATION:

• D73
• D22
• O12
• O43

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1 In this paper corruption and bribery is used synonymously. Lobbying is however different from bribery on the pretext that it is legal and tantamount to lending information and expertise to politicians so that policies get framed to favor of the lobbyist (Campos and Giovannoni 2007). For further distinction between lobbying and corruption refer to Bennedsen and Feldmann (2006) and Dahm and Porteiro (2008).

2 Using 2005 and 2012–14 BEEPS survey, lobbying index is constructed by taking an average of questions coded as ecaq44a, ecaq44b and ecaq44c while bribery index is derived from question coded as ecaq39.

3 Institutional efficiency index is one component of Global competitive index published annually by World Economic Forum.

4 The first stage IV regression results in Table C1 correspond to regression estimates presented in column (3) of Table 3.

5 For statistical validity of the selected instruments refer to discussion presented in Section 5.1.

6 The data from the 2002 and 2009 surveys could not be utilized because of missing values pertaining to some of our main variables of interest. For example, the 2002 survey lacks information on the cost of labor and raw materials therefore making the estimation of production function not possible. Similarly, the 2009 survey lacks information on the measure used for construction of lobbying index in our study.

7 De Rosa, Gooroochurn, and Gorg (2010 derive these results using 2009 EBRD-World Bank Business Environment and Enterprise Performance Survey (BEEPS) for 28 transition and developed economies.

8 Blagojević and Damijan (2013) uses pooled data from 2002–2009 BEEPS surveys from 27 transition economies.

9 Using the results in column (1) and taking the first differential of dependent variable with respect to bribery index yields: $\raisebox{1ex}{$\partial \left(ln \frac{Y}{L}\right)$}\!\left/ \!\raisebox{-1ex}{$\partial \mathit{Bribery} \mathit{Index}$}\right.$= −0.173 + 0.164*High income.

10 Firms classified as having a high bribery index are taken to have a score greater than or equal to 4 whereas firms having a high lobbying index are taken to have a score greater than or equal to 3.