With funding from the Global Development Network and the Inter-American Development Bank, Lucas Ronconi and I have recently finished some a first cut at an analysis of land use regulations in a large number of developing countries. We have tried (and are still trying) to make use of World Bank survey data on 683 cities around the world. The abstract is below.
Abstract: Theoretical predictions of negative impacts of stringent land use regulation on urbanization outcomes have contributed to reform efforts around the world. However, there is limited empirical evidence internationally on the relationship between regulation and urbanization, especially in developing countries. In this report, we present a series of stylized facts about the prevalence, determinants and impacts of land use regulation in Asia, Latin America, and the rest of the world. In order to do this, we combine several data sources, including surveys of regulation from the World Bank, remote sensing data, and data from various countries’ censuses. The largest variation in regulations is across countries and regions rather than across continents or within countries. Economic development is negatively correlated with land use regulations, even after controlling for the general regulatory environment. Cities that are more constrained by water and mountains tend to have more regulations. Other major determinants are legal systems and urbanization pressures. Regulations are not clearly associated with measures of urban form such as population density or urban compactness, but they do seem to negatively impact business expansion and household formation.
I am excited to have joined the Department of Urban Planning at the UCLA Luskin School of Public Affairs; one of my almae matres and a center for innovative and important scholarship, research and teaching. See what’s new here at http://publicaffairs.ucla.edu/.
My thoughts on the housing policy of Hong Kong’s new Chief Executive featured in the article here.
A working paper that reflects on the nature of housing deficits and explores the concept in the Indonesia case. A copy can be found on SSRN here and the abstract is below. Comments are welcome!2>
The idea of a housing deficit is a common, seemingly objective frame for housing policies. A deficit of between 3 and 8 million units in Indonesia has become a concern for the government in recent years. The wide range of estimates demonstrates not only that the methods used to estimate housing need are inconsistent, but also that the meaning of the term housing deficit is little understood. Insufficient housing supply is generally blamed for the supposed deficit, and policies to stimulate housing production have been considered in response. This paper analyzes household formation trends in urban Indonesia from 1990 to 2007 and estimates the quantitative housing deficit based on trends. The analysis finds that an abrupt change in the rate of household formation and household size occurred in Indonesia around the year 2000, suggesting that beyond macro trends in the country’s demographic transition and urbanization, the economic and political upheavals in the last years of the 20th century affected household formation significantly. Yet, analysis of household formation over different socioeconomic groups and urban areas shows that housing markets do also matter.
A second paper on segregation in Hong Kong is entitled Creating Mixed-Income Neighborhoods Unintentionally: Public Housing Residualization and Socioeconomic Segregation in Hong Kong. A copy can be found here and the abstract below.
Public housing affects the segregation of ethnic and socioeconomic groups in different ways in different cities, depending on the residents and its location. This paper analyzes how Hong Kong’s public housing system affects segregation by income using a combination of methods, including indexes that explicitly account for space and the ordinal nature of income data. Findings show that public housing unintentionally reduces the city’s spatial segregation, though the effect varies across space and income groups. The spatial distance between low-income and middle-income households is reduced, creating mixed-income neighborhoods but also increasing the segregation of high-income households.