Does corruption matter for stock markets? The role of heterogeneous institutions
Shrabani Saha and
Keshab Bhattarai ()
Economic Modelling, 2021, vol. 94, issue C, 386-400
In examining the role of institutions in resisting corruption and its impact on growth, most studies concentrate on the aggregate level and conclude that sound institutions enhance growth. We focus instead on varying dimensions of heterogeneous institutions in the presence of corruption and their interactive effect on stock returns in four emerging economies: Brazil, Russia, India, and China (BRIC). We pay particular attention to democratic accountability, bureaucratic quality, and law and order. Using monthly data for the first time in this literature, we find that corruption and other weaker institutions lower stock returns during the period 1995–2014. However, interaction effects show interesting mixed results: Bureaucratic quality can mitigate the ill effects of corruption and increase returns by reducing red tape, whereas corruption distorts law and order and lowers stock returns. Our findings suggest that policies to enhance bureaucratic efficiency can abate the adverse effects of corruption, but a restrictive law and order environment tends to lower stock returns.
Keywords: Institutions; Stock returns; BRIC countries; Growth; Corruption (search for similar items in EconPapers)
JEL-codes: A13 G15 G18 O16 O17 P16 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:94:y:2021:i:c:p:386-400
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().