View source for De Figueiredo Edwards (2007) - Does Private Money Buy Public Policy

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*This page is referenced in [[BPP Field Exam Papers]]


==Reference(s)==
de Figueiredo, R. J. P. Jr. and G. Edwards (2007), Does Private Money Buy Public Policy? Campaign Contributions and Regulatory Outcomes in Telecommunications, Journal of Economics and Management Strategy 16, 547-576 [http://www.edegan.com/pdfs/deFigueiredo%20Edwards%20(2007)%20-%20Does%20Private%20Money%20Buy%20Public%20Policy.pdf pdf]

[https://sites.google.com/site/examsupplement/dE09279A.pdf?attredirects=0 SLIDES] from Rui's presentation in class


==Abstract==
To what extent can market participants affect the outcomes of regulatory policy? In this paper, we study the effects of one potential source of influence - campaign contributions - from competing interests in the local telecommunications industry, on regulatory policy decisions of state public utility commissions. Using a unique new data set, we find, in contrast to much of the literature on campaign contributions, that there is a significant effect of private money on regulatory outcomes. This result is robust to numerous alternative model specifications. We also assess the extent of omitted variable bias that would have to exist to obviate the estimated result. We find that for our result to be spurious, omitted variables would have to explain more than five times the variation in the mix of private money as is explained by the variables included in our analysis. We consider this to be very unlikely.


==Summary==

The paper examines UNE (Unbundled Network Element) local loop prices. The prices are regulated but the loops are owned by incumbents (monopolies). Regulators are implicitly directed by legislators, and incumbents and entrants provide campaign contributions to legislators. Incumbents and entrants have different ideal points in terms of prices, and they are modelled (implicitly) as playing a two-principal/single-agent game as in [[Baron 2001 - Theories of Strategic Nonmarket Participation | Baron (2001)]]. 


==Empirical model==

The model is:

<math>LoopPrice_{i,t} = \alpha +\beta Contributions_{i,t} + \gamma_1 Costs_i + \gamma_2 Ideologies_{i,t} + \gamma_3 Demographics_i + \gamma_4 Institutions_{i,t} + \epsilon_{i,t}\,</math>


The variables are:
*<math>Contributions_{i,t}\,</math>: percentage of contributions attributable to entrants in state <math>i\,</math>, cycle <math>t\,</math>.
*<math>Costs_i\,</math>: FCC estimates of local loop costs
*<math>Ideologies_{i,t}\,</math>: Commission, Legislative and Gubernatorial ideologies - republican vs. democrat
*<math>Demographics_i\,</math>: Percentage of Business lines, and percentage of meteropolitan population
*<math>Institutions_{i,t}\,</math>: Whether the regulatory commission is elected or appointed, and whether price cap (or rate of return) regulation is applied


Results:
*After state and cycle fixed effects are imposed there is a highly statistically significant negative relationship between current cycle contributions and prices (higher contributions imply lower prices, and vice versa).
*The coefficient is increased if previous cycle contributions are also included
*The results withstand various robustness checks (see page 567)
*Instrumentation using a rank-based measure of contributions leads to similar results
*Casuality is 'determined' by the use of lagged values
*Ommited Variable Bias is addressed using a technique from Altonji et al. (2002) - it suggests that unobservables would have to have a five times stronger effect than observables to undermine the results.