Comparing Homicide‐Suicides in the United States and Sweden

Research on homicides followed by suicides has largely relied on very localized samples and relatively short time spans of data. As a result, little is known about the extent to which patterns within cases of homicide‐suicides are geographically specific. The current study seeks to help fill this gap by comparing twenty years of homicide‐suicide data for Sweden and a large U.S. county. Although some of the underlying patterns in the two countries are similar (e.g., decreasing rates), a number of important differences emerge, particularly with respect to incidence, weapons used, perpetrator age, and relationship of the perpetrator to the victim.     

The Experience of the Infant Entering Refuge (Shelter) Setting with Their Mothers After Fleeing Family Violence

Journal of Family Violence - Almost nothing is known about how the infant may experience being in a women’s Refuge (Shelter) setting with their mother after fleeing family violence, despite...     

How do firms use innovations to hedge against economic and political uncertainty? Evidence from a large sample of nations

The Journal of Technology Transfer - Using data on 135 countries, this paper studies the determinants of process innovation introduction, focusing on the impacts of economic and political...     

Evaluating the economic impact of a special credit programme: KIK/KMKP in Indonesia

This article discusses a study of the economic impact of Indonesia's KIK/KMKP programme of special credits for small‐scale enterprises. Our major focus is on how to measure economic impact. It discusses the concept of ‘impact’, the survey design, the statistical framework, and the practical problems of implementation, and briefly summarises the findings. We believe that our methodology generated reasonably reliable data and fundamentally sound estimates of the credit programme's direct impact on employment, output and income.     

Credit scores,race, and residential sorting

Credit scores have a profound impact on home purchasing power and mortgage pricing, yet little is known about how credit scores influence households' residential location decisions. This study estimates the effects of credit scores on residential sorting behavior using a novel mortgage industry data set combining household demographic, credit, and financial data with property location information and detailed community attribute data. I employ the data set to estimate a discrete‐choice residential sorting model. I find that credit scores significantly predict residential sorting behavior and models that do not account for credit score provide biased estimates of housing utilities for black households in particular. Simulation results show that increases in credit score are associated with increases in the consumption of higher‐priced homes in more expensive school districts, higher‐quality public schools, and proximity to urban/metropolitan areas. © 2010 by the Association for Public Policy Analysis and Management.