Can the internet reduce corruption? A cross-country study based on dynamic panel data models

Abstract This study attempts to estimate the effects of internet adoption on reducing corruption by using a panel consisting of 70 countries covering the period from 1998 to 2005. The results of Granger causality tests reveal that, while causality running from internet adoption to corruption reduction can be established, the causality between internet adoption and corruption is bi-directional. To deal with the problem of endogeneity, the dynamic panel data (DPD) models are employed. The estimation results show that the effects of internet adoption on corruption reduction are statistically significant but not too substantial. Our findings suggest that the internet has shown a capacity for reducing corruption, but its potential has yet to be fully realized.

[1]  G. Tabellini,et al.  Electoral Rules and Corruption , 2001, SSRN Electronic Journal.

[2]  Meng-Chun Liu,et al.  Social Learning and Digital Divides: A Case Study of Internet Technology Diffusion , 2006 .

[3]  W. Newey,et al.  Estimating vector autoregressions with panel data , 1988 .

[4]  Nigel Scott,et al.  Good Practice Paper on ICTs for Economic Growth and Poverty Reduction , 2005 .

[5]  H. Vinod.  Statistical analysis of corruption data and using the Internet to reduce corruption , 1999 .

[6]  Macmillan India Limited.  Tackling corruption, transforming lives : accelerating human development in Asia and the Pacific , 2008 .

[7]  Jean Tirole,et al.  A Theory of Collective Reputations (with applications to the persistence of corruption and to firm quality) , 1996 .

[8]  Myungsin Chae,et al.  Varying criticality of key success factors of national e-Strategy along the status of economic development of nations , 2009, Gov. Inf. Q..

[9]  M. G. Quibria,et al.  Digital Divide: Determinants and Policies with Special Reference to Asia , 2003 .

[10]  M. Arellano,et al.  Another look at the instrumental variable estimation of error-components models , 1995 .

[11]  Clay G. Wescott,et al.  E‐Government in the Asia‐pacific region , 2001 .

[12]  Ajit Mishra.  Persistence of corruption: some theoretical perspectives , 2006 .

[13]  Danila Serra,et al.  Empirical determinants of corruption: A sensitivity analysis , 2004 .

[14]  Rumel S. Mahmood.  Can Information and Communication Technology Help Reduce Corruption? How So and Why Not: Two Case Studies from South Asia , 2004 .

[15]  M. Arellano,et al.  Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations , 1991 .

[16]  Political Pressure on the Bundesbank: An Empirical Investigation Using the Havrilesky Approach , 2002 .

[17]  A. Drobny.  Real Wages and Employment: Keynes, Monetarism and the Labour Market , 1988 .

[18]  Raymond J. Fisman,et al.  Decentralization and Corruption: Evidence Across Countries , 2000 .

[19]  R. Paul Sturges,et al.  Corruption, Transparency and a Role for ICT? , 2004 .

[20]  Daniel Treisman,et al.  The causes of corruption: a cross-national study , 2000 .

[21]  R. Blundell,et al.  Initial Conditions and Moment Restrictions in Dynamic Panel Data Models , 1998 .

[22]  Laszlo Konya,et al.  Exports and growth: Granger causality analysis on OECD countries with a panel data approach , 2006 .

[23]  Yogesh Kumar Dwivedi,et al.  Guest editorial: From implementation to adoption: Challenges to successful E-Government diffusion , 2009, Gov. Inf. Q..

[24]  M. Justesen.  The effect of economic freedom on growth revisited: New evidence on causality from a panel of countries 1970-1999 , 2008 .

[25]  Marcin Piatkowski,et al.  Can Information and Communication Technologies Make a Difference in the Development of Transition Economies , 2006 .

[26]  Seongcheol Kim,et al.  An institutional analysis of an e-government system for anti-corruption: The case of OPEN , 2009, Gov. Inf. Q..

[27]  A. Brunetti,et al.  A free press is bad news for corruption , 2003 .

[28]  Rafael Di Tella,et al.  Rents, Competition, and Corruption , 1999 .

[29]  C. Granger.  Investigating Causal Relations by Econometric Models and Cross-Spectral Methods , 1969 .

[30]  Institutions and the External Capital Structure of Countries , 2004 .