WHY ARE URBAN TRAVEL TIMES SO STABLE?

Personal travel time in U.S. urban areas has been stable, clashing with the assertion that urban sprawl greatly lengthens travel. Average commute time rises by 7.7 percent with each cross‐sectional doubling of Metropolitan Statistical Area (MSA) jobs. Using the RELU‐TRAN structural computable general equilibrium model of the Chicago MSA, we simulate the equilibrium effects of a 24 percent population increase projected from 2000 to 2030 by the Chicago Metropolitan Agency for Planning. If no new road capacity is added, then congestion per mile increases. Although the urbanized land area increases by 19 percent, indicating sprawl, the vehicle miles traveled (VMT) per car‐trip decreases by 1.31 percent and the VMT per car‐trip to work decreases by 2.78 percent. Car travel time increases by only 6.25 percent and commuting time by only 4.54 percent, from 30.3 minutes in 2000 to 31.7 in 2030 or 3.4 seconds per year. We further explore the effects of new road capacity, gasoline prices, public transit speed, fuel economy gains, limits on suburban construction, and importantly, the cross‐elasticity of public transit use with respect to car times. The availability of public transportation, economizing on nonwork travel, and land use adjustments that increase job‐residence proximity keep times stable.     

ARE ACADEMIC MODELS OF URBAN SERVICE DISTRIBUTIONS RELEVANT TO PUBLIC POLICY?: LESSONS FROM NEW YORK

Studies identifying and explaining the patterns of service allocations within cities have proliferated in recent years. Methodologies have been refined and the quality of data has improved. Theories of service distribution tested in the research are largely of three types: (1) those that stress “underclass” explanations of racial, economic and/or political discrimination; (2) those that stress service conditions or neighborhood needs; and (3) those that stress bureaucratic decision rules. This article presents findings on the determinants of intra-city distribution patterns for sanitation, fire and police services in New York. These findings highlight some of the difficulties of existing explanations and suggest that a bureaucratic decision rule (BDR) model provides more guidance in interpreting frequently confusing and contradictory results. Though specific rules are hard to identify, use of the BDR model enables more meaningful policy recommendations.     

DOES AGGLOMERATION MATTER EVERYWHERE?: NEW FIRM LOCATION DECISIONS IN RURAL AND URBAN MARKETS*

We test whether commonly used measures of agglomeration economies encourage new firm entry in both urban and rural markets. Using new firm location decisions in Iowa and North Carolina, we find that measured agglomeration economies increase the probability of new firm entry in both urban and rural areas. Firms are more likely to locate in markets with an existing cluster of firms in the same industry, with greater concentrations of upstream suppliers or downstream customers, and with a larger proportion of college‐educated workers in the local labor supply. Firms are less likely to enter markets with no incumbent firms in the sector or where production is concentrated in relatively few sectors. The same factors encourage both stand‐alone start‐ups and establishments built by multiplant firms. Commuting decisions exhibit the same pattern as new firm entry with workers commuting from low to high agglomeration markets. Because agglomeration economies are important for rural firm entry also, policies encouraging new firm entry should focus on relatively few job centers rather than encouraging new firm entry in every small town.     

IS CRIME BAD FOR BUSINESS? CRIME AND COMMERCIAL PROPERTY VALUES IN NEW YORK CITY

To test how crime affects economic activity, we use point‐specific data on crime, commercial property sales and assessed values from New York City, relying on an instrumental variables strategy. We find that crime reduces commercial property values, and the magnitude of the effect depends on the type and geography of crime. Elasticities range from ?0.1 to ?0.5. We find stronger evidence for negative violent crime effects in neighborhoods with lower incomes and higher shares of minority residents. Thus, disadvantaged neighborhoods are doubly harmed by crime—they have higher crime rates and those crimes have stronger effects on economic activity.     

FROM KARLO-LIBKNEKHTOVSK AND NEW YORK TO PROPOYSK AND RASTYAPINO?: HOW PLACE NAMES ARE CHANGING IN THE FORMER USSR

In a paper submitted directly to Post-Soviet Geography, the author presents as thorough a list of place name changes as possible for the former USSR for the period 1985 to mid-1992. The situation is assessed with respect to the former union republics, nationality-based lower-order administrative territorial units, oblasts and krays, and major cities and urban settlements. The list appears to represent the most thorough and authoritative compilation of its kind yet published in the West, given the absence of any official body now empowered with the approval and registration of place name changes across the entire geographic space of the former USSR.     

BORDERS AS BOUNDARIES TO FISCAL POLICY INTERACTIONS? AN EMPIRICAL ANALYSIS OF POLITICIANS’ OPINIONS ON RIVALS IN THE COMPETITION FOR FIRMS

Studies of spatial policy interdependence in (local) public policies usually concentrate on the relations between jurisdictions within a single analyzed region, and disregard possible extraregional effects. However, the theoretical spatial statistics literature shows that biased estimates might emerge if spatial interactions extend beyond the boundaries of the available data (i.e., the boundary value problem). This paper empirically assesses the practical relevance of this concern by studying German local politicians’ assessments of their jurisdictions’ main competitors in the struggle to attract firms. We find that location near a border significantly undermines politicians’ perception that the fiercest competitive pressure derives from jurisdictions within their own state. This effect sets in about 20 km (10.2 km) from a national (international) border. These results indicate that nearest municipalities perceive each other as competitors regardless of the state or country where they are located, which has important implications for estimating spatial dependence models.