This paper develops a framework for inferring common Markov-switching components in a panel data set with large cross-section and time-series dimensions. We apply the framework to studying similarities and differences across U.S. states in the timing of business cycles.
We explore the influence of city-level business cycle fluctuations on crime in 20 large cities in the United States. Our monthly time-series analysis considers seven crimes over an approximately 20-year period: murder, rape, assault, robbery, burglary, larceny, and motor vehicle theft.
We use non-parametric distribution dynamics techniques to reassess the convergence of per capita personal income (PCPI) across U.S. states and across metropolitan and nonmetropolitan portions of states for the period 1969-2005.
We present a model of crime where two municipalities exist within a metropolitan statistical area (MSA). Consistent with the literature, local law enforcement has a crime reduction effect and a crime diversion effect.
Municipalities have revenue motives for enforcing traffic laws in addition to public safety motives because many traffic offenses are punished via fines and the issuing municipality often retains the revenue.
Existing research has found an inverse relationship between urban density and the degree of income inequality within metropolitan areas, suggesting that, as cities spread out, they become increasingly segregated by income.
Local authorities in North Carolina, and subsequently in at least 23 other states, have enacted laws intending to reduce predatory and abusive lending. While there is substantial variation in the laws, they typically extend the coverage of the Federal Home Ownership and Equity Protection Act (HOEPA) by including home purchase and open end mortgage credit, by lowering annual percentage rate (APR) and fees and points triggers, and by prohibiting or restricting the use of balloon payments and prepayment penalties.
We find that the magnitudes of the regional effects of monetary policy were considerably dampened during the Volcker-Greenspan era. Further, regional differences in the depths of monetary-policy-induced recessions are related to the concentration of the banking sector, whereas differences in the total cost of these recessions are related to industry mix.
We apply spatial econometric techniques to models of state and local fiscal policy convergence. Total tax revenue and expenditures, as well as broad tax and expenditure categories, of state and local governments in each of the 48 contiguous U.S. states are examined.
Human capital is typically viewed as generating a number of desirable outcomes, including economic growth. Yet, in spite of its importance, few empirical studies have explored why some economies accumulate more human capital than others. This paper attempts to do so using a sample of more than 200 metropolitan areas in the United States over the years 1980, 1990, and 2000.
This paper demonstrates that levels of entrepreneurship can be greatly affected by the general policy environment. Using a state-level panel, we estimate the effects of several policy variables on rates of entrepreneurship and find that bankruptcy exemptions, corporate tax rates, and the level of the minimum wage all affect a state's rate of entrepreneurship.
This paper presents new evidence of spatial correlation in U.S. state income growth. We extend the basic spatial econometric model used in the growth literature by allowing spatial correlation in state income growth to vary across geographic regions. We find positive spatial correlation in income growth rates across neighboring states, but that the strength of this spatial correlation varies considerably by region.