Special Interest Capture of Regulatory Agencies: A Ten‐Year Analysis of Voting Behavior on Regional Fishery Management Councils

This article tests capture theory by analyzing voting behavior on U.S. Regional Fishery Management Councils. Some seats on the councils are reserved for state and federal agency representatives; others, for political appointees. The political appointees primarily represent special interests (specifically, commercial and recreational fishing interests); a smaller number of appointees represent public interests. We use logistic regression to model the vote of state and federal agency representatives on the councils as a function of the votes of commercial interests, recreational interests, and public interests. We find evidence that some state agencies are captured by special interests from their states, but not systematic evidence across all states. We find that state agency representatives voted with commercial interests from their own state in five of the sixteen states in our sample; with recreational interests in three states; and with both special interests in two states. These ten states support the capture hypothesis; the other six states do not. We find no evidence that federal agencies were captured on the councils. We conclude that the gubernatorial‐driven appointment process leads to capture at the state level by promoting voting blocs among state agency representatives and special interests from those states. Federal agency representatives, by contrast, are better able to maintain their distance from state‐level politics on the councils, and thereby enhance their ability to vote independently on fishery management measures.     

THE ENVIRONMENTAL PERFORMANCE OF POLLUTING PLANTS: A SPATIAL ANALYSIS*

ABSTRACT This paper uses plant‐level EPA and Census data to examine spatial factors affecting environmental performance, as measured by air pollutant emissions and regulatory compliance. We find significant effects for compliance, but not for emissions. Compliance is positively spatially correlated, partly explained by spatial correlations in observed plant characteristics, suggesting influences of industry agglomeration. The use of spatial econometric methods shows only small effects of spatially lagged compliance status, and does not greatly change the estimated contributions of other spatially explicit factors. Regulatory activity has the expected effect of increasing environmental performance, both at the inspected plant and at neighboring plants, but only for plants in the same state, demonstrating the importance of jurisdictional boundaries.     

THE SPATIOTEMPORAL EVOLUTION OF U.S. CARBON DIOXIDE EMISSIONS: STYLIZED FACTS AND IMPLICATIONS FOR CLIMATE POLICY

We characterize the evolution of U.S. carbon dioxide (CO₂) emissions using an index number decomposition technique which partitions the 1963–2008 growth of states’ energy‐related CO₂ into changes in five driving factors: the emission intensity of energy use, the energy intensity of economic activity, the composition of states’ output, per capita income and population. Compositional change and declining energy intensity attenuate emissions growth, but their impacts are offset by increasing population and income. Despite absolute interstate divergence in both emissions and their precursors, states’ emission‐ and energy intensities—and ultimately, CO₂—appear to be stochastically converging. We assess the implications of these trends using a novel vector autoregression (VAR) emission forecasting technique based on our index numbers. The resulting emission projections are comparable to, but generally exceed, those forecast by the 2010 EIA Annual Energy Outlook.     

Industry Influence in Stakeholder‐Driven State Climate Change Planning Efforts

Drawing from the literature on public participation and stakeholder collaboratives, this article investigates the influence of power and wealth, as well as political and economic context on the output of stakeholders advisory committees convened to formulate state greenhouse gas (GHG) mitigation policies. Using small sample regression techniques, we analyze the outputs of stakeholder groups in 18 states that have completed Climate Action Plans to reduce GHGs. We find that an increase of 1 percent in the number of energy industry representatives that participate in Climate Action Councils significantly predicts a 4 percent reduction of GHG mitigation targets for the energy sector. More surprisingly, the results also show that where the utilities represent a larger share of the state economy, the Climate Action Plans identify more aggressive GHG reduction goals for the energy sector. We also find that the political orientation of the executive of the state is not correlated with GHG mitigation requirements for the energy sector, suggesting that GHG mitigation is less partisan at the state level than in Washington, DC. We find no evidence that state wealth is associated with GHG mitigation requirements. Finally, we suggest additional research needed to clarify the role of stakeholder participation processes in the evolving arena of climate change policy.     

REGULATORY FEDERALISM AND THE DISTRIBUTION OF AIR POLLUTANT EMISSIONS*

ABSTRACT Recent empirical work suggests that (i) incomes are converging through time, and (ii) income and pollution levels are linked. This paper weds these two literatures by examining the spatial and temporal distribution of pollution. After establishing that theoretical predictions about whether pollution will converge are critically linked to certain structural parameters, we explore pollution convergence using state‐level data on two important pollutants—nitrogen oxides and sulfur oxides—from 1929 to 1999. We find stronger evidence of converging emission rates during the federal pollution control years (1970–1999) than during the local control years (1929–1969). These results suggest that income convergence alone may not be sufficient to induce convergence of pollutant emissions.     

A Spatiotemporal Bayesian Hierarchical Approach to Investigating Patterns of Confidence in the Police at the Neighborhood Level

Public confidence in the police is crucial to effective policing. Improving understanding of public confidence at the local level will better enable the police to conduct proactive confidence interventions to meet the concerns of local communities. Conventional approaches do not consider that public confidence varies across geographic space as well as in time. Neighborhood level approaches to modeling public confidence in the police are hampered by the small number problem and the resulting instability in the estimates and uncertainty in the results. This research illustrates a spatiotemporal Bayesian approach for estimating and forecasting public confidence at the neighborhood level and we use it to examine trends in public confidence in the police in London, UK, for Q2 2006 to Q3 2013. Our approach overcomes the limitations of the small number problem and specifically, we investigate the effect of the spatiotemporal representation structure chosen on the estimates of public confidence produced. We then investigate the use of the model for forecasting by producing one‐step ahead forecasts of the final third of the time series. The results are compared with the forecasts from traditional time‐series forecasting methods like naïve, exponential smoothing, ARIMA, STARIMA, and others. A model with spatially structured and unstructured random effects as well as a normally distributed spatiotemporal interaction term was the most parsimonious and produced the most realistic estimates. It also provided the best forecasts at the London‐wide, Borough, and neighborhood level.     

Trading Speed for Accuracy? Managing Goal Conflict and Accommodation in the U.S. Unemployment Insurance Program

Public managers must often cope with competing and conflicting goals. The common formulation is to assume that managers must trade‐off goals against each other. But is this always true? An alternative hypothesis is that sometimes managers may instead be able to improve outcomes on multiple goals simultaneously—by altering management practices. We test this “trade‐off” notion using a panel of state‐level administrative data from the U.S. unemployment insurance (UI) system from 1997 to 2004 and qualitative interviews from selected states. The trade‐off examined is timeliness of UI benefit payments versus the quality of UI determinations. In general, we find that state administrators often adopt management practices that facilitate improved outcomes for both timeliness and quality, indicating no trade‐off but instead a synergy between outcomes. We also find evidence of a feedback effect linking higher performance on timeliness to better quality determinations.     

LONG-TERM FORECASTING OF NONCOINTEGRATED AND COINTEGRATED REGIONAL AND NATIONAL MODELS*

ABSTRACT. Johansen's (1988) multivariate test for cointegration is first applied to four models involving quarterly state data and five variables, along with a national model based on Friedman and Kuttner's (1992) model of money demand, which uses three variables. Each regional model consists of frequently used national and state series, for which theory suggests the possible cointegration of several series pairs. Beginning with all five series, however, one state model is found to be cointegrated over each of 20 successive estimation intervals. The money demand model and one state model are not cointegrated over the same intervals. In the cointegrated case, five-year experimental forecasts show that error correction mechanism (ECM) and Bayesian ECM models outperform all other approaches. More importantly, forecasting performance improves further by respecifying the ECM model based on three cointegrated series pairs rather than the five-component cointegrating vector. For the two noncointegrated systems, the first-difference model suggested by the cointegration/ error correction literature is far superior to VAR in levels over both shortand long-term horizons.     

PROBLEMS OF THE LEVEL OF THE CASPIAN AND THE STABILITY OF ITS SHORELINE

The first of two papers on the problem of forecasting the level of the Caspian Sea evaluates factors widely believed to have been responsible for its lowering during much of the present century (including tectonic movements, climatic cycles, human activity). It concludes that previous forecasts have been inaccurate because of the failure to adequately model the complexity of processes involved, specifically the internal mechanisms of “self-regulation” of water levels. Continuation of the recent slight rise in the Caspian's level is predicted at least into the early 1990s (translated by Andrew R. Bond).     

CONVERGENCE AND THE U.S. STATES: A TIME-SERIES ANALYSIS*

ABSTRACT. After decades of apparent convergence, state and regional per capita earnings diverged between 1978 and 1988. A central tenet of the convergence hypothesis is that shocks to relative state and regional earnings, such as those of the 1978 to 1988 period, are transitory. We find evidence for convergence for the U.S. states and regions during the 1929 to 1990 period after allowing for a break in the rate at which the various states and regions were converging in 1946. An important finding of this research is that the US. states and regions achieved per capita earnings convergence by 1946.     

INCOME INEQUALITY,ECONOMIC GROWTH,AND THE DISTRIBUTION OF INCOME GAINS: EVIDENCE FROM THE U.S. STATES*

ABSTRACT This paper first investigates a relationship between economic growth and income inequality using U.S. states data, a state cost‐of‐living deflator, and nonlinearity. It then explores the distribution of income gains among different income groups. We find that the impact of inequality on growth is nonlinear. Lowering inequality or increasing it substantially reduces growth; thus stable inequality may be good for growth. Economic growth affects incomes of the poor, the middle‐income group, and the rich similarly with the elasticity of one. Education and labor market policies become important in promoting growth and improving income gains of the poor.     

CHANGES IN THE LOCATION OF EMPLOYMENT AND OWNERSHIP: EVIDENCE FROM CALIFORNIA*

ABSTRACT We use the National Establishment Time‐Series database to describe shifts in the geographic dispersion of employment and ownership of firms. Focusing on data on business establishments in California, and establishments anywhere in the United States that are owned by firms headquartered in California, we find shifts in the operations of businesses headquartered in California to other states. However, this shift has been offset by increased employment in the state by firms headquartered elsewhere, resulting in California's share of national employment holding quite constant. The evidence points to increasing geographic dispersion of firms' operations, especially in industries with lower communication costs.     

A ROBUST APPROACH TO PREDICTING FLUCTUATIONS IN STATE-LEVEL EMPLOYMENT GROWTH*

ABSTRACT. Economic forecasting models are famous for performing well over short time periods and then suffering rapidly deteriorating performance when economic conditions change. This behavior makes composite forecasting models valuable in situations where large forecast errors cause considerable losses. A composite forecasting model for state-level employment is proposed here. This method is designed to protect state budget processes by producing robust forecasts of changes in employment and the related revenue collections. An application to Georgia nonagricultural employment is presented which demonstrates the benefits of this technique. The example shows that the method can forecast such series accurately without the forecaster having to choose in advance a single model specification to all economic conditions.     

THE POLITICAL TRADE‐OFF BETWEEN ENVIRONMENTAL STRINGENCY AND ECONOMIC DEVELOPMENT IN RURAL AMERICA*

ABSTRACT We examine the impact of the political trade‐off between rural economic development and environmental quality on the determination of environmental regulations in the U.S. intensive livestock industry. The political economy model, adapted from Fredriksson (1997) , is tested empirically, using state‐level data on environmental regulation of the U.S. livestock sector. We find that state governments respond to greater potential for water pollution with more stringent environmental regulations. Consistent with our political economy model, we also find that states with lower recent growth in per capita income implement less stringent environmental regulations.     

Enhancing the Sustainability and Earthquake Resistance of Confined Masonry Dwellings: The Case of El Salvador

The seismic vulnerability of housing stock in El Salvador was demonstrated during the recent 2001 earthquakes. Relative to other types of common residential construction, confined masonry dwellings performed well. A coordinated pilot study was conducted with the objective of improving the seismic resistance of this form of construction while reducing associated costs and greenhouse gas emissions. Laboratory tests examined brick strength in relation to firing temperature and duration. Analytical studies examined the potential for voided bricks to improve seismic performance, the reduction in demands associated with stiffening the roof diaphragm, and demands imposed on the roof bracing system. This pilot study identifies the potential for voided bricks to reduce construction costs and greenhouse gas emissions with negligible effects on performance. The addition of end-bay diagonal bracing at the roof level resulted in significant performance enhancements.     

Laboratories of (In)equality? Redistributive Policy and Income Inequality in the American States

Prior literature has emphasized demographic, economic, and political explanations for increasing income inequality in the United States, with little attention paid to the role of state‐level policy. This is despite great variation across states in both the level of inequality and the rate at which it is rising. This paper asks whether differences in state policy choices can help explain this variation; specifically, we examined a range of state redistributive policies enacted between 1980 and 2005 and identified four common approaches likely to impact inequality: taxes on the wealthy, taxes on the poor, spending on the poor, and labor market policies. We used pooled cross‐sectional time‐series data and a fixed‐effects model to assess the relationship between states’ use of each policy approach and two measures of market income inequality: the Gini coefficient and the income share of the top 1 percent. We find policies played a significant role in shaping income inequality in the states. For three of these four policy approaches, we found less inequality following expansions of state redistributive policy. Yet, for another, we identified the opposite pattern. These findings highlight the importance of state policy choices in shaping market inequality, and have implications for designing state policies to reduce income inequality since the success of these efforts depends on the policy approach used to redistribute income and wealth.     

THE EFFECTS OF TRADE WITH DEVELOPING COUNTRIES ON THE REGIONAL DEMAND FOR SKILL IN THE U.S.: EVIDENCE FROM COUNTY DATA*

ABSTRACT Using county‐level data from the 1980s and 1990s and a county‐level trade measure that incorporates the county's industrial mix and patterns of international trade across industries, I provide new evidence that trade with developing countries raises the demand for skill and the skill premium in the U.S. Consistent with Heckscher–Ohlin, I find that trade driven by differences in factor endowments has an economically significant impact on local labor markets. The evidence suggests that when trade with developing countries rises, counties with higher skill endowment and greater employment in industries with larger trade shares experience greater relative demand for high‐skilled labor.     

Multilevel Instruments for Infrastructure Investment: Evaluating State Revolving Funds for Water

In recent decades, the federal government has introduced complex, multilevel state‐operated revolving loan fund programs as an instrument for promoting state and local investment in national infrastructure priorities while limiting direct federal involvement in implementation. A federally funded state revolving fund (SRF) program combines features of a categorical matching grant to states and a subsidized loan program to localities, both of which should lower the effective price of infrastructure investment and therefore promote higher levels of infrastructure investment. However, little evidence exists to date on whether these programs stimulate new subnational spending or instead displace spending that would have occurred otherwise. We evaluate the stimulus effects of SRFs by examining the two largest such programs, the Clean Water and the Drinking Water SRF Programs. Analyzing 17 years of state‐level panel data, we find evidence that the flow of federal funds to states under the SRF programs stimulates new local investment in wastewater infrastructure, but not in drinking water infrastructure. In discussing several possible explanations for these divergent results, we argue for further research that emphasizes the intergovernmental features of this financing tool.     

LOCAL FOOD,URBANIZATION, AND TRANSPORT‐RELATED GREENHOUSE GAS EMISSIONS

We argue that “buying local” does not necessarily reduce transport‐related greenhouse gas emissions, even if production technologies and yields are homogeneous in space. We develop a partial‐equilibrium model of rural‐urban systems where the spatial distribution of food production within and between regions is endogenous. We exhibit cases where locating some food production in the least‐urbanized regions results in lower emissions and higher welfare than if all regions are self‐sufficient. The optimal spatial allocation of food production does not exclude the possibility that some regions should be self‐sufficient, provided that their urban population sizes are neither too large nor too small.     

Green cities? Urbanization,trade, and the environment

Is urbanization good for the environment? This paper establishes a simple core–periphery model with monocentric cities, which comprises key forces that shape the structure and interrelation of cities to study the impact of the urban evolution on the environment. We focus on global warming and the potential of unfettered market forces to economize on emissions. The model parameters are chosen to match the dichotomy between average “large” and “small” cities in the urban geography of the United States, and the sectoral greenhouse gas emissions recorded for the United States. Based on numerical analyzes we find that a forced switch to a system with equally sized cities reduces total emissions. Second, any city driver which pronounces the asymmetry between the core and the periphery drives up emissions in the total city system, too, and the endogenous adjustment of the urban system accounts for the bulk of the change in emissions. Third, none of the city drivers gives rise to an urban environmental Kuznets curve according to our numerical simulations. Finally, the welfare‐maximizing allocation tends to involve dispersion of cities and the more so the higher is the marginal damage from pollution.