Levy Economics Institute

This essay assesses the relationship between farm size and productivity. Both parametric and nonparametric methods are used to derive efficiency measures. Smaller farms are found to have higher net farm income per hectare, and to be more technically efficient, than larger farms.

This paper examines the claim that the land rental market can be an effective means of redistributing access to, if not ownership of, land to the rural poor, using Paraguay as our model. The land sales market is also examined. The land rental market in Paraguay's rural areas is found to be very thin, due at least in part to a lack of available credit for inputs. Renting-in substantial amounts of land is found to contribute significantly to household per-capita income.

This paper summarizes the background, type, logic, and working procedure of the statistical matching used in the Levy Institute Measure of Economic Well-Being (LIMEW) project to combine the various data sets used to produce the synthetic data set with which the LIMEW is constructed. We use the match between the 2001 Survey of Consumer Finances and Annual Demographic Survey of Current Population Survey data sets to demonstrate the procedure and results of the matching. Challenges facing the use of this technique, such as the distribution of weights, are discussed in the conclusion.

Most empirical studies of economic deprivation and inequality in developing countries are based on narrow measures of economic well-being, such as personal consumption or money income. These types of measures have several notable shortcomings. They do not reflect access to public services such as education or transportation. They capture self-provisioning only minimally. In addition, conventional measures do not capture the advantages from asset ownership and disadvantages imposed by debt burden. A substantial literature has emerged in the recent years on the measurement issues and estimation of broader measures of household economic well-being, with an almost exclusive focus on the advanced capitalist countries. The primary purpose of this paper is to make the case for applying broader measures of well-being to the measurement of inequality in developing countries. We discuss methodological issues regarding the treatment of individual components of the measure; statistical issues involved in combining information from various surveys via statistical matching; and issues of data availability for specific countries.

We construct estimates of the Levy Institute Measure of Economic Well-Being for France for the years 1989 and 2000. We also estimate the standard measure of disposable cash income (DI) from the same data sources. We analyze overall trends in the level and distribution of household well-being using both measures for France as a whole and for subgroups of the French population. The average French household experienced a slower rate of growth in LIMEW than DI over the period. A substantial portion of the growth in well-being for the middle quintile was a result of increases in net government expenditures and income from wealth. We also found that the well-being of families headed by single females relative to married couples deteriorated much more, while the well-being of households headed by the elderly relative to households headed by the nonelderly improved much more than indicated by the standard measure of disposable income. The conventional measure indicates that a steep decline in economic inequality took place between 1989 and 2000, while our measure indicates no such change. We argue that these outcomes can be traced to the difference in the treatment of the role of wealth in shaping economic inequality. Our measure also indicates that, on balance, government expenditures and taxes did not have an inequality-reducing effect in France for both years. This is, again, contrary to conventional wisdom.

The quality of match of four statistical matches used in the LIMEW estimates for Great Britain for 1995 and 2005 is described. The first match combines the fifth wave of the British Household Panel Survey (BHPS) with the 1995-96 Family Resources Survey (FRS). The second match combines the 1995 time-use module of the Office of Population Censuses and Surveys Omnibus Survey with the 1995-96 FRS. The third match combines the 15th wave (2005) of the BHPS with the 2005 FRS. The fourth match combines the 2000 United Kingdom Time Use Survey with the 2005 FRS. In each case, the alignment of the two datasets is examined, after which various aspects of the match quality are described. In each case, the matches are of high quality, given the nature of the source datasets.