William B. Stronge

U.S. tourism in Mexico: An empirical analysis

Abstract This study estimated demand functions for tourism by U.S. residents in Mexico border areas, the Mexican interior, and overseas. There was no evidence that U.S. tourists substitute Mexico for more distant destinations as transportation costs rise. Border tourism is income elastic when the share of U.S. income of the border states is held fixed. Tourism in the Mexican interior is also income elastic. Tourism along the border is price elastic, while tourism in the interior is elastic with respect to U.S. and overseas prices but inelastic with respect to Mexican prices. The rise in the share of the Mexican interior in U.S. overseas tourism is not related to price factors. Recent devaluations of the Mexican peso are unlikely to provide benefits to the Mexican tourism industry.

Some Law Enforcement Operations Implications of Crime Seasonality

Abstract Criminal justice system policy makers have recently begun to utilize sophisticated techniques of analysis to explore questions of resource allocation and program evaluation.1, 2, 6, 8, 10 All too often, however, the benefits of such techniques have been denied to the large proportion of criminal justice units which lack access to extensive computer facilities and large technical staffs. This paper illustrates how one important crime data time series property—seasonal variation— may be adjusted for and utilized with some fairly simple procedures. The police operations and planning implications of the presence of seasonality in crime data are then examined. The authors develop their discussion with reference to seasonal variation in monthly data on major crimes for a large United States urban area, Miami, Florida. The time period of the study is 1949–1972.

Spectral analysis of reported crime data

This paper applies spectral analysis to data on reported crimes for a medium-sized city. The objective is to examine certain aspects of the statistical properties of crime data, as well as to illustrate the utility of the spectral-analytic method for criminal justice research. A discussion of the theoretical underpinnings of the spectral analysis technique is provided through analogy with familiar least squares regression methods. Both spectral and cross-spectral analysis are then employed to test selected hypotheses concerning the data.

Testing for seasonality in reported crime data

Abstract In spite of the apparent importance of crime statistics to policy-makers and the public, these data are not often analyzed or refined in the same manner as other social series such as unemployment. In this paper, seasonal variation in FBI index crimes is investigated for a major urban area. Using Miami data for 1949–1970, a test for seasonality is developed and seasonal indices are constructed for a number of crime types. A definite seasonal pattern in Miami crime data is found to exist, although its importance seems to be declining in recent years. Some applications of seasonally adjusted data to public information and operations are also briefly discussed.

Metropolitan Inflation in the United States 1961–1978

This paper examines the rate of price inflation in twenty-two U.S. metropolitan areas over the 1961–1978 time period. A Phillips-Lipsey model containing specifications for unemployment, expected inflation, and imported inflation is evaluated for each region. The data are examined cross-sectionally as well as serially and little evidence is found to contradict the hypothesis that the rate of price inflation observed in U.S. metropolitan areas is the national rate. Local unemployment and expectations are generally insignificant explanators. A statistical problem associated with the use of the lagged dependent variable in a cross section regression is also discussed.