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The purpose of this paper is to explore why school districts in the USA made so little use of local sources of non-tax revenues, even when faced with declines in traditional revenue as occurred during the Great Recession? The analysis uses the case of Colorado, where historically districts have made more use of alternative revenues.

Data for the analysis are drawn from the NCES’s Common Core of Data with administrative data to create a panel of Colorado school districts. The paper presents estimates of traditional panel models, as well as spatial panel models, that give the correlates of variation in alternative revenue for education.

As is true nationally, in Colorado school districts made no increased use of non-tax revenues in fiscal downturns, while the presence of expenditure limits does increase use, though not as might be expected. Revenues from overrides of the limits and alternative local revenues appear to be complements. Further, there is no evidence of spatial relationships for the alternative revenue sources considered.

This paper uses richer data than has ever been used to explore the determinants of alternative revenues, making it possible to explore relationships others could not. In addition, synthetic cohort analysis is used to generate plausible instrumental variables for passage of an override of an expenditure limitation. Further, no existing analysis of nontraditional revenues considers the possibility that use of those revenues might be spatially correlated.

This paper aims to build on existing studies on the relationship between individual wages, age and experience, and provide new evidence on the determinants of wages in Italy.

Wage‐age profiles, which include cohort variables to capture generational differences in wages and are characterised by a changing‐over‐time structure, are estimated by fixed and random effects panel regressions. The analysis exploits a longitudinal dataset of administrative data on wages for the period 1985‐1999.

This paper shows that wage to age profiles for different cohorts of workers are not stable over time: although younger generations of Italian workers are benefiting from higher starting wages than older generations, they face the prospect of lower growth of future earnings. It also confirms the existence of a significant supply effect: the bigger the cohort relative to the active population, the smaller the cohort's gain in terms of wage levels. Finally, it captures the dependence of individual wages on aggregate labour market conditions: individual wages are shown to be negatively related to the unemployment rate and positively related to the union wage index.

Although the paper does not propose a novel theoretical approach to individual wage analysis, it demonstrates the benefits of a more integrated empirical analysis of individual wages.

The empirical findings suggest that it would be possible and useful to integrate the changing age profiles of individual wages with the estimation and projections of Italian aggregate industry and service sector average wages.

The paper provides new evidence on the determinants of the dynamics of individual wages through the estimation of time‐varying wage to age profiles of workers in the Italian industry and service sectors.

This study estimates earnings function parameters across alternative occupational paths, with an emphasis on identifying rates of return to post-school human capital investment. Based on cross-sectional and synthetic cohort analysis using the 1973–2000 Current Population Surveys, estimates are obtained for men and women on the returns to schooling and the investment intensity, length, and returns from post-school training. Although the shapes of wage-experience profiles differ substantially across occupations and skill groups, evidence supports the theoretical prediction that rates of return are equivalent across alternative investment paths. Little evidence is found for an increase in returns to post-school training over time. By the 1990s, returns to schooling had risen to a level similar to the returns from post-school training.

This paper investigates, theoretically and empirically, differences between blacks and whites in the United States concerning the intergenerational transmission of occupational skills and the effects on sons’ earnings. The father–son skill correlation is measured by the correlation coefficient (or cosine of the angle) between the father’s skill vector and the son’s skill vector. The skill vector comprises an individual’s occupational characteristics from the Dictionary of Occupational Titles (DOT). According to data from the U.S. National Longitudinal Survey of Youth (NLSY79), white sons earn higher wages in occupations that require skills similar to those of their fathers, whereas black sons in such circumstances incur a wage loss. A large portion of the racial wage gap is explained by the father–son skill correlation. However, a significant unexplained racial wage gap remains at the lower tail of the wage distribution.

The purpose of this paper is to find the effects of human capital inequality on economic growth.

Thailand Labor Force Survey has been used to generate provincial average years of schooling and Gini coefficient of years of schooling for the years 1995‒2012. Econometric techniques have been employed to identify the effects of human capital inequality on economic growth.

Economic growth is inversely affected by the distribution of human capital in Thailand. The coefficient of human capital inequality suggests that if Gini coefficient increases by 0.01 points, gross provincial product (GPP) decreases by about 2 percentage points in the long run. However, the effect of average years of schooling in GPP is not significant.

There is a lack of strong theoretical background for the relationship between human capital inequality and economic growth to support the empirical study.

The findings of the study help to design and evaluate education policies in developing countries like Thailand and other low- and middle-income countries.

This paper is among the first attempts to analyze the effect of human capital inequality on economic growth with sub-national level annual data. In addition, it considers cross sectional dependence in panel model.

The paper examines the evolution of beginning farms’ income statement and balance sheet items over a 15-year period. The purpose of this paper is to gain insight into the diversity of beginning farms from a financial point of view.

Using the USDA’s Agricultural Resource Management Survey (ARMS), the author constructs a synthetic panel of data consisting of age cohorts of beginning farmers and follow them over time. Baseline financial information for the farm income statement and balance sheet is examined in 1999 and again in 2014 for each cohort.

Overall, there is a marked contrast in the evolution in the income statement between beginning farmers who are under 45 years old and those over 45. The gross cash income of the youngest cohorts grows tremendously, as do their expenses, indicating rapid expansion in production on the part of the youngest cohorts. The change in the balance sheets of the cohorts also provides a glimpse into the changing roles of beginning famers over time. The youngest cohort of beginning farmers increase the current and non-current assets on their balance sheets by a substantial amount, more than doubling both. Furthermore, the youngest cohort is the only group to take on more current liabilities, indicating increased financing of the production expenses.

Differences in the evolution of financial profiles of beginning farms may predict differences in future output, and it could be a predictor of the farm’s operational goals or intentions, as well as predictor of future financial needs and challenges.

Knowing and understanding likely trajectories of beginning farmers may provide an opportunity to better tailor farm programs, outreach, and support to beginning farmers.

The purpose of this paper is to estimate the impact of Internal Revenue Code cost recovery provisions – Section 179 and “bonus depreciation” – on farm capital investment.

The authors construct a synthetic panel of data consisting of cohorts of similar farms based on state and production specialization using the USDA’s Agricultural Resource Management Survey for years 1996-2012. Employing panel data methods, the authors are able to control for time-invariant fixed effects, as well as the effects of past investment on current investment.

The authors estimate statistically significant investment demand elasticities with respect to the Section 179 expensing deduction of between 0.28 and 0.50. A change in bonus depreciation, on average, had little impact on capital investment.

The estimates suggest there is a modest effect of the cost recovery provisions on investment overall, but a stronger effect on farms that have more than $10,000 in gross cash farm income. There are other implications for the agricultural sector: the provisions may encourage technology adoption with its associated benefits, such as reduced cost of production and improved conservation practices. On the other hand, the policy could contribute to the growing concentration in production as large commercial farms expand their operated acreage to take advantage of increasingly efficient physical capital.

To the authors’ knowledge, this is the first research to use a nationally representative dataset to estimate to impact of Section 179 and “bonus depreciation” on farm investment. The findings provide evidence of the provisions’ impact on farm capital purchases.

This paper aims to measure the financial impact on social security system of a recently proposed indexation mechanism for retirement age by considering the Italian longevity experience. The analysis is motivated by the progressive increase in life expectancy at advanced age, which is rapidly bringing to the fore noticeable socio-economic consequences in most industrialized countries. Among those, the impact on National Social Security systems is particularly relevant if people live longer than expected; this will lead to greater financial exposure for pension providers.

Referring to the Italian population for illustrative purposes, the authors contemplate different scenarios for mortality projection methods and for the implementation of pension age shift while accounting for gender and cohort gaps and model risk. Synthetic indicators to measure the impact of the indexation mechanism on social security system are introduced on the basis of pension cash flows.

An indexation policy that manages gender gap while adjusting retirement age for varying life expectancy is proposed. As a result, sustainability of public retirement expenditure is improved.

The paper is a concise scenario analysis of the reduction of costs and risks that pension providers would have if the system resorted to link retirement age to life expectancy. The ideas fostered by the paper follow a recent proposal of the Authors on a flexible retirement scheme that deals with model risk for mortality projection and accounts for gender gap in mortality rates.