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Notes
- 1.
Although they may not offer the same quasi-experimental advantages as does the local exchange sector, any sector where institutions expose producers to non-market distributional influences faces this type of risk (e.g., insurance, which we will investigate in Chapter 5). Fred McChesney (1987) carefully anticipated this important possibility.
- 2.
Altonji, Elder, and Taber’s (2005) method appears well-suited to aiding identification in the present application. First, although campaign finance restrictions exhibit considerable cross-state variation, they appear more stable when evaluated within states across time. In addition, the considerable cost of adjusting sunk telecom investments means that our proxy for output (i.e., land-line connections to telecommunications networks) likely exhibits noisy time series variation (e.g., variable lags in responding to stimuli) that can cloud evidence of causal relationships (even if they truly exist). Insight to whether campaign finance restrictions can strengthen economic performance thus appears unlikely to come from the time series dimension of relevant variables. Finally, because our regressors of interest are institutional proxies and theories of endogenous institutions are not very well-developed, good instruments can be difficult to find for the present application.
- 3.
Regulatory jurisdiction over telecommunications policy divides itself between the Federal Communications Commission (FCC) and state public utility or public corporation commissions. States maintain authority over most rates charged to customers for local exchange services. For long-distance services, the FCC regulates interstate service and state regulatory or public utilities commissions regulate intrastate service (Harris and Kraft 1997).
- 4.
- 5.
Nationwide, 12 states elect their public utility commissioners. Others employ an appointment process (Council of State Governments 1999).
- 6.
Since 1989, several states’ legislatures have statutorily constrained utility commissions’ authority over telecommunications rates and revenues (Zearfoss 1998). Gerald Brock (1994) argued that such channels for “micromanagement” effectively transform elected legislators into “independent telecommunication policy makers” (independent, that is, of associated regulators).
- 7.
To see how caps can expand campaign finance activities, consider an all-pay auction where high-valuation players confront a binding cap. By formally reducing feasible bids for “high-valuation” players, such a constraint might be expected to reduce aggregate bidding. But capping high types can also encourage low-valuation players to enter the game. Indeed, absent a constraint, low-valuation players can find their equilibrium probability of winning so low that submitting a bid of “zero” becomes optimal. By encouraging low-valuation players to submit strictly positive bids in equilibrium, caps can thus increase the level of bidding from all players.
- 8.
Rui de Figueiredo and Geoff Edwards (2007) found evidence that, on its face, appears to support this channel – that is, actual contributions influence prices in the hypothesized direction. As modeled in our Chapter 1, however, capital-accumulation decisions ultimately rest on campaign contribution laws (i.e., the potential for consumer or producer influence). In addition, de Figueiredo and Edwards gained identification from time series variation in prices. The technology that exposes local exchange carriers to the capital levy problem, however, also creates considerable adjustment costs and thus diminishes the responsiveness of investment to high-frequency price changes.
- 9.
Contributors (reviewed above) to the public choice literature found a negative relationship between retail price indexes and consumers’ potential to pressure regulators. If an increase in such pressure decreases an investment-relevant price, then received indexes would have indeed exhibited a negative relationship with electoral accountability. However, such indexes would also be noisy proxies for investigations (like the present one) that focus on how laws influence economic performance (rather than distributions). In this plausible case, measuring variables with error could mask the theoretically robust relationships outlined in Chapter 1, even if those relationships are empirically important.
- 10.
- 11.
To be sure, theory is making progress, but does little to help the present identification problem. Besley and Case (2003) and Thomas Stratmann and Francisco Aparicio-Castillo (2006), for example, used party preference and educational attainment as instruments for campaign finance laws. In our application, however, education can independently relate to equilibrium output through its effect on consumer demand whereas party preference can do so through unobserved policy channels. Channels like these for independent influence can create considerable bias. For example, in unreported 2SLS regressions where measures of education and party preference act as instruments (as opposed to controls), output and consumer pressure continue to share a significant and negative relationship (as they do in corresponding OLS regressions). The coefficient estimates’ magnitude, however, is implausibly large.
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Falaschetti, D. (2009). Natural Experiments. In: Democratic Governance and Economic Performance. Studies in Public Choice, vol 14. Springer, New York, NY. https://doi.org/10.1007/978-0-387-78707-7_2
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