This article reports a research finding that lesbians in Australia earn an unexplained wage premium of 0%–13%, whereas gay men experience an unexplained negative wage gap of 8%–18%. Based on data from the Australian household panel Household Income and Labour Dynamics in Australia, the article is the first to establish these gaps in Australia, and to examine the degree to which credence can be afforded to claims that endowments such as personality traits may help explain such wage differentials. Using ordinary least squares and Blinder–Oaxaca decomposition methods, the study explicitly includes the battery of Big Five personality traits in wage regressions and estimates the contribution of endowments and returns to these traits. The finding is that personality traits and returns to them do not differ along lines of sexual orientation. Gay men in particular suffer a substantial unexplained wage penalty in the workplace. Such unexplained differences suggest that discrimination on the basis of sexual orientation, though unlawful, may exist in Australia.

A recent trend in rural development policy emphasizes small business development in place of industrial recruitment. To analyze some of the likely effects of expanding the proportion of small firms in local economies, an empirical wage rate model incorporating employer size was developed, and parameters were estimated using household data from rural Putnam County, Georgia. The estimates indicated that large employers offered higher wages than small employers and that the wage premium they offered was greater for blacks than for whites. These results support Thomas Till's argument that southern rural counties with relatively large black populations should not abandon efforts to attract large employers. Other factors associated with higher wages included level of education, previous labor force experience, and employment in certain occupations and industries.

Regular hired farm workers, performing 150 days or more of farm work annually, became increasingly important in the 1970's. The number of regular hired workers in the United States increased by almost 50 percent during the decade, while the number of seasonal workers, operators, and unpaid family workers declined. Pricing of regular hired labor is investigated through estimation of three nested wage determination models in a case study analysis for Georgia. Micro-level data on individual workers were used to analyze the effects of general human capital, farm worker duties, local labor market conditions, and farm characteristics on wage rates.

Shimer (Mismatch, American Economic Review 97, 1074–1101 [2007]) introduced a model of mismatch in which limited mobility of vacant jobs and unemployed workers provides a microfoundation for their coexistence in equilibrium. He assumed that the short side of a local labor market receives all the gains from trade. In this note I show that modifying this assumption on wage-setting can deliver more reasonable predictions for wages at the level of the local market and in the aggregate.

Industrial production and employment in Italy were hard hit by the Great Depression, and remained below trend until at least 1936. Few quantitative studies have been conducted on the causes of Italy's recession and slow recovery. Using monthly data, and reviving an aggregate supply model published in Bernanke and Carey [Quarterly Journal of Economics 111 (1996), 853–883], we empirically test whether Italy's 1930s industrial performance could be related to the Fascist wage and price policies, which, aiming at keeping workers' real wages constant, actually raised firms' labor costs, computed as nominal wages deflated by wholesale prices, hence stalling industrial production. We find evidence of a strong countercyclicality of real wages and of nominal wage stickiness in the period 1929–1936, which would confirm our hypothesis. Trade restrictions are found to play a smaller role in hindering industrial production than previously stated in the literature, whereas we confirm the weak transmission of financial turbulence to the real economy.