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The cyclical behavior of US crime rates reflects the dynamics of crime in the country. This paper aims to investigate the US's club convergence of crime rates to provide insights into whether the crime rates increased or decreased over time. The paper also analyzes the factors influencing the probability of states converging to a particular convergence club of crime.

The analysis is based on balanced panel data from all 50 states and the district of Columbia on violent and property crime rates covering 1976–2019. This yields a cross-state panel of 2,244 observations with 55 time periods and 51 groups. In addition, the author used a club clustering procedure to investigate the convergence hypothesis in the study.

The empirical results support population convergence of violent crime rates. However, the evidence that supports population convergence of property crime rates in the study is not found. Further analysis using the club clustering procedure shows that property crime rates converge into three clubs. The existence of club convergence in property crime rates means that the variation in the property crime rates tends to narrow among the states within each of the clubs identified in the study. Analysis based on an ordered probit model identifies economic, geographic and human capital factors that significantly drive the state's convergence club membership.

The central policy insight from these results is that crime rates grow slowly over time, as evident by the convergence of violent crime and club convergence of property crime in the study. Moreover, the existence of club convergence of property crime is an indication that policies to mitigate property crime might need to target states within each club. This includes the efforts to use state rather than national crime-fighting policies.

As crimes are committed at the local level, this study's primary limitation is the lack of community-level data on crime and other factors considered. Analysis based on community-level data might provide a better representation of crime dynamics. However, the author hopes to consider this as less aggregated data are available to use in future research.

The paper provides new insights into the convergence of crime rates using the club convergence procedure in the USA. This is considered an improvement to the methods used in the previous studies.

This study aims to investigate the causal relationship between nutrition and economic growth in sub-Saharan Africa.

A dynamic panel causality test based on the Blundell-Bond’s system generalized methods-of-moment was used. To make efficient inference for the estimates, the authors check for the panel unit root and co-integration relationship amongst the variables.

The variables were found to be non-stationary at level, stationary after first difference and co-integrated. The results of the causality tests reveal evidence of long and short-run bidirectional causality between nutrition and economic growth, which implies that nutritional improvement is a cause and consequence of economic growth and vice versa.

This is the first study to consider causality between nutrition and economic growth in the region.

This study aims to address two research questions. First, do the agricultural extension services have an impact on the potential outcomes considered in the primary studies, and to what extent? Second, how sensitive is the reported impact to the study-specific characteristics in the primary studies?

The paper synthesizes 45 studies that assessed the causal impact of agricultural extension services published in 2004–2021, using meta-regression analysis. It considers three measures of effect sizes – Cohen’s, Hedges and principal correlation coefficient (PCC) – to standardize the reported impact of agricultural extension services in the primary studies.

The empirical results show that, on average, agricultural extension services have statistically significant and positive impacts on the potential outcomes identified in the primary studies. However, the magnitude of the impact is considered medium-sized. Other results show that the effect size estimates of agricultural extension services' impact significantly vary with the data type (cross-sectional data vs. panel data), research design (non-experimental vs. experimental design) and econometric methods employed in the primary studies.

One can argue that the medium-sized impact we estimated indicates evidence of a moderate, weak relationship between agricultural extension services and the potential outcomes considered in the primary studies. This means that agricultural extension services need to be restructured in the current form to stimulate change in the agricultural sector globally. In addition, the sensitivity of effect sizes to study attributes (i.e. data types, research design and econometric methods) shows that researchers and academicians need to pay attention to these attributes to provide more reliable estimates for policy purposes.

This is the first study that attempts to shed light on the overall performance of agricultural extension services using a meta-regression analysis approach.

The COVID-19 pandemic has caused many households to experience income shocks because of the unprecedented job loss, resulting in the demand for public and private food assistance programs and a surge in unemployment insurance filing in the USA. This study aims to investigate the association between social safety programs (e.g. supplementary nutritional assistance programs (SNAP), unemployment insurance and charitable food assistance) and household food sufficiency during the COVID-19 pandemic in the country.

The authors used the Household Pulse Surveys (HPS) conducted by the US Census Bureau from August 2020 to March 2021. And, the authors used an ordered probit model for the empirical analysis because the indicator of food sufficiency constructed from the HPS is an ordinal variable with four categories. The indicator identifies four groups of households: severe food insufficiency, moderate food insufficiency, mild food sufficiency and food sufficiency.

The results show that food sufficiency is significantly higher among the SNAP, unemployment insurance and charitable food assistance recipients than non-recipients. Furthermore, the results indicate that food sufficiency is significantly lower among black, Asian, Hispanic and other races than white households. Concerning the intersectional effect of social safety net programs and race/ethnicity on household food sufficiency, the authors find that the household food sufficiency is significantly higher among white, black and Asian households who benefited from SNAP, compared with non-beneficiary households. On the other hand, the authors find no evidence that participation in SNAP increases food sufficiency significantly among Hispanics and other races. In addition, the likelihood of food sufficiency increases significantly among white, black, Asian, Hispanic and other races that received unemployment insurance and charitable food assistance during the COVID-19 pandemic compared with those who did not benefit from the programs.

These results underscore the critical role collective America’s social safety net programs played in increasing food sufficiency among Americans during the COVID-19 pandemic. Specifically, the results suggest that families' basic needs (food sufficiency) would have been at risk if these safety net programs were not available to households during the pandemic. This, therefore, highlights the important role that government- and non-government-supported food emergency assistance programs can play in preventing people from facing food insufficiency problems in a tough time or during a crisis in the USA.

This study highlights the dynamic relationship between Americans’ social safety net programs and household food sufficiency during the COVID-19 pandemic.

The purpose of this paper is to revisit the Environmental Kuznets Curve (EKC) model in Sub-Saharan Africa (SSA) countries by focusing on two indicators of environmental change (EC), namely rate of deforestation (RD) and all greenhouse gas emissions from agriculture (Agric_GHG) with aim of addressing two key objectives in the study. First, to investigate whether the EKC hypothesis exists for both indicators considered in the region. Second, to examine the effects of macroeconomic and institutional variables on both indicators in the study.

The authors employ a balanced panel data covering 43 countries from 1990-2009 in the study. Subsequently, the study uses serial correlation/autoregressive order one corrected cross-section time series model based on Feasible Generalized Least Square method.

The empirical results show that the EKC exists (i.e. as inverted U-shaped) only for all GHG emissions from agriculture. Agricultural production and trade openness increase significantly both indicators of EC considered in the study. Other results show that, population growth reduces significantly Agric_GHG, while economic growth increases significantly RD in SSA.

This is the very first study to investigate the applicability of EKC hypothesis to emissions from non-oil sector such as agriculture (i.e. all GHG emissions from agriculture) in the region.

The purpose of this paper is to examine how the intakes of calories, proteins, and fats vary with income in sub-Saharan Africa (SSA).

Annual time series data for 43 countries covering 1975-2009 that yields a balanced panel was employed for analysis. Nutrient-income elasticities are estimated based on the aggregate Engel Curve framework, using a feasible generalized least squares (FGLS) technique that is robust to autocorrelation.

The estimated nutrient-income elasticities are small: a 10 percent increase in income will lead, respectively, to rises of about 0.73, 0.87, and 0.90 percent in calories, proteins, and fats intake; showing that policies that are aimed at eliminating malnutrition through only the growth of per capita income will have positive but limited impacts. The estimated aggregate Engel Curve and the non-parametric plots show that at higher income levels the relationship between income and nutrient intake is non-linear and diminished, suggesting a low likelihood for the manifestation of an obesity epidemic in SSA.

This is the very study that attempts to look at the nutrition-income elasticities at cross-country level in SSA.

The purpose of this paper is to use cross-country data to investigate whether convergence process exists in per capital nutrient supply and also identify the determinants of change in per capita nutrient supply in sub-Saharan Africa (SSA).

Annual time series data for 43 countries covering 1975-2009 that yields balanced panel were employed for the analysis. The convergence hypothesis is examined based on the neoclassical growth model using feasible generalized least square approach that is robust to autocorrelation and cross-sectional dependence.

The empirical results lend support to existence of convergence process in nutrient supply in SSA. Evidence of convergence in nutrient supply may have contributed to observed reduction in incidence of food-poverty in the region, which aligns with the argument in literature that recent Africa food security gains are due to food imports. The results of the determinants of change in nutrient supply showed that, global food trade represented by trade openness consistently increased growth in nutrient supply across countries in SSA significantly. Meanwhile, the speed of convergence of per capita nutrient supply, which measures how quickly growth in nutrient supply increases over time is very low, as this calls for urgent policy attention in the region.

The very first study to investigate convergence in food consumption and nutritional supply in SSA.

The aim of this study is in twofolds. First, to take a critical look at nutrient consumed and its trends and second, to examine the relationship between share of nutrient consumed across selected food groups and per capita income in Nigeria.

The author uses seemingly unrelated regressions.

The result of the first objective reveals that the average calorie, protein and fat intakes were still below the recommended daily allowance since the 1960s as diets in Nigeria remained very much cereal-based over the years. Also, the results of objective two show that calorie, protein, and fat share of animal products respond positively but inelastic to the per capita income growth in Nigeria over the years.

Contrary to previous studies, the present study is designed not to fit aggregated nutrient demand from various food items as a function of income, but to relate the nutrient share of each homogenous and heterogeneous food product categories to the aggregated nutrient intake from these food groups and per capita income in Nigeria.

The purpose of this paper is to examine cost efficiency and its determinants in Nigerian sawmill industries.

A stochastic frontier model is employed on a total of 160 mills randomly selected across five states in south‐western Nigeria in 2006.

The results show an estimated average cost efficiency of 1.262. This suggests that an average mill incurs about 26 per cent costs above the frontier cost when processing planks from logs. Further analysis indicates that a significant level of cost ineffisciency is present in Nigeria's sawmilling industry. Analysis of determinants of cost efficiency reveals that more years of education, experience, age, and level of capital investment reduce cost inefficiencies between 7 and 16 per cent. Sawmill operation is found to be associated with economies of scale in the study area.

The paper contributes to existing studies on the efficiency of sawmill industries in Nigeria by taking a holistic assessment of the industry from a cost perspective.

The purpose of this paper is to identify the trends in crop diversification (CD) while examining its impact on the technical efficiency of peasant farmers in Nigeria.

The paper employs the Herfindahl and Ogive indices to compute the diversification indices and the stochastic frontier production model (SFPM) to estimate the technical efficiency (TE) level of the farms using unbalanced panel data covering three farming seasons (2006/2007 to 2008/2009).

The results of both the Herfindahl and Ogive indices showed that cropping pattern increased significantly with the intensification of crop diversification in the study across the three seasons. The result of the SFPM shows evidence of decreasing returns‐to‐scale and technical progress in the food crop production in the region. Education, extension, and CD are identified as efficiency increasing policy variables while an average TE level of about 81 percent was obtained from the analysis.

To the best of the author's knowledge, this the very first study that employs panel data to analyze technical efficiency of farms in Nigeria.