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This paper aims to investigate the changes in living standard among families with different socio-economic status in China with the use of Engel's Coefficient. The authors develop a decomposition methodology to figure out the driving forces behind changes in Engel's Coefficient, and investigate how dramatic economic growth, volatile food price and rapid nutrition transition affect living standard among different families.

The authors propose a statistical method to decompose the changes in living standard measured by Engel's Coefficient into structure effect, price effect, quantity effect and income effect. Using the China Health and Nutrition Survey data between 2000 and 2011, the authors estimate these four effects by employing a decomposition method.

Results show that Engel's Coefficient in China decreased by 8.7 percentage points (hereafter “pp”) during 2000–2011, where structure effect leads to 0.2 pp increase, price effect results in 17.7 pp increase, quantity effect brings about 12.4 pp decline and income effect contributes to 14.2 pp decline. Results indicate that rising food prices are the main obstacle to improve households' living standard. Typically, poor and rural families' living standard is more vulnerable to the rise in food prices, and they benefit less from income growth.

This study proposes a decomposition method to investigate the determinants of change in Engel's Coefficient, which provides a deeper understanding of how economic growth, food price change and nutrition transition affect people's living standard in different socio-economic groups in developing countries. This study also provides valuable insights on how to achieve common prosperity from the perspective of consumption upgrading.

The purpose of this paper is to review the theoretical background, methodological extensions, and empirical applications of the Engel curve, which is applied to the research of the change in farmers’ welfare and food demand in China after the economic reform in 1978, compared with the statistics of income and food consumption.

This paper mainly uses the traditional method of Engel curve, which is compared with income growth and food consumption, to study farmers’ welfare improvement in rural China.

The Engel coefficients identify three different stages for farmers’ welfare change after 1978. The first stage is the period between 1978 and 1988, in which farmers’ welfare has been continuously enhanced due to the institutional bonus of the 1978 economic reform and increased government purchase price of agricultural products. The second stage is the period between 1989 and 1995, in which farmers’ welfare has been slightly deteriorated mainly due to the end of institutional reform bonus, suppressed food prices, relative high inflation, and instable political situation. The third stage is the period after 1995, in which farmers’ welfare returns to a growing path, as the dual price system was abolished, the transition from a planned economy to a market economy had been completed, and the government carried out protective policies for agriculture and started to heavily subsidize agriculture. The Engel coefficient still remained at a very high level at 0.59 in 1995, but it continuously decreased to 0.33 in 2015. The welfare enhancement for farmers mainly results from deepened market-oriented reform, protective policies for agriculture, and prevalent off-farm employment. The Engel coefficient is also linked to food demand elasticities. Along with the decreasing Engel coefficient in the past 40 years, income elasticities also continuously decrease from 0.55 in 1978 to 0.08 in 2015. Food demand is very inelastic now, and any further increase in income will not substantially increase food demand any more.

Inequality has not been analyzed.

This paper reviews the methodological advantages of the Engel curves, and uses it to identify different stages of welfare change and estimate income elasticities of food demand for farmers in China after the 1978 economic reform.

Economic theories on structural change focus on factors such as fluctuations in relative prices and income growth. In addition, China’s reform and opening up has also been accompanied by increasing openness, significant fluctuations in investment rates, and frictions in the labor market. Existing literature lacks a unified theoretical framework to assess the relative importance of all these determinants. The paper aims to discuss these issues.

To incorporate all of the potential determinants of China’s structural change, the authors build a two-country four-sector neoclassical growth model that embeds the multi-sector Eaton and Kortum (2002) model of international trade, complete input-output structure, non-homothetic preference and labor market frictions. The authors decompose the sectoral employment shares into six effects: the Baumol, Engel, investment, international trade, factor intensity and labor market friction effects. Using the data of Chinese economy from 1978 to 2011, the authors perform a quantitative investigation of the six determinants’ effects through the decomposition approach and counterfactual exercises.

Low-income elasticity of demand, high labor intensity, and the existence of the switching costs are the reasons for the high employment share in the agricultural sector. Technological progress, investment and international trade have comparatively less influence on the proportion difference of employment in the three sectors.

Therefore, to examine the impact on China’s structural change, in addition to Baumol effect and the Engel effect, it is also necessary to consider the impact of three more factors: international trade, investment and switching costs. Therefore, the authors decompose the factors that may influence China’s structural change into the Baumol, Engel, investment, international trade, factor intensity effect and switching cost effects. The authors evaluate these six effects using the decomposition approach and counterfactual exercises.

Within the last 15 years, law enforcement agencies have increased their collection of data on vehicle stops. A variety of resource guides, research reports, and peer‐reviewed articles have outlined the methods used to collect these data and conduct analyses. This literature is spread across numerous publications and can be cumbersome to summarize for practical use by practitioners and academics. This article seeks to fill this gap by detailing the current best practices in vehicle stop data collection and analysis in state police agencies.

The article summarizes the data collection techniques used to assist in identifying racial/ethnic disparities in vehicle stops. Specifically, questions concerning why, when, how, and what data should be collected are addressed. The most common data analysis techniques for vehicle stops are offered, including an evaluation of common benchmarking techniques and their ability to measure at‐risk drivers. Vehicle stop outcome analyses are also discussed, including multivariate analyses and the outcome test. Within this summary, strengths and weaknesses of these techniques are explored.

In summarizing these approaches, a body of best practices in vehicle stop data collection and analysis is developed.

Racial profiling continues to be a contentious issue for law enforcement and the community. A considerable body of research has developed to assess the prevalence of racial profiling. This article offers social scientists and practitioners a comprehensive, succinct, peer‐reviewed summary of the best practices in vehicle stop data collection and analysis.

It is the objective of this paper to elaborate determinants of food expenditure patterns for the generation 50+ in Germany on the basis of an Engel‐curve analysis.

Survey data for Germany are taken from the Survey of Health, Ageing and Retirement (SHARE) database. Food‐at‐home (FAH) expenditures of the generation 50+ are explained within a multiple regression analysis first. Then, a double‐hurdle approach based on the probit model and a truncated regression are utilized for reproducing the existence of food‐away‐from‐home (FAFH) expenditures and the share of FAFH expenditures on consumption expenditures across households. Available information on socio‐demographic variables, income and the health status of the respondents are introduced as regressors in the multivariate analyses.

FAH expenditures in the generation 50+ in Germany follow the theoretical expectations underlying Engel functions. With a rising income level, FAH expenditures increase as well but the income share of FAH expenditures declines as does the share of FAH expenditures in total food expenditures. Apart from income, the share of FAH expenditures in food expenditures rises with age, household size, and it is highest for the lowest education level. Moreover, it is higher for West than for East German households. Becoming a pensioner increases absolute FAH expenditures, but does not affect the FAH expenditure share significantly. Very different results are provided by the Engel‐curve analysis for food away from home. A rising income raises FAFH expenditures, whereas becoming a pensioner lowers it. The age variable is insignificant.

The estimated Engel curves suggest that food at home grows less with rising income than food away from home. In particular, the determinants of the per‐capita FAFH expenditures reveal important determinants of expenditures of the generation 50+ in a highly dynamic consumption category. The results have important marketing implications.

Despite the growing economic importance of the generation 50+ in industrialised countries, empirical evidence on how this age group behaves in its food expenditure pattern is often lacking. This study provides a first set of estimated coefficients from Engel curves for Germany. These show how income as well as sociodemographic and health variables affect per‐capita expenditures for FAH and FAFH consumption.

The purpose of this paper is to attempt to replicate Engel’s (2001) styles of supervision using data from a new sample and including additional independent variables.

The data were collected from a sample of police supervisors (N=369) at three distinct locations throughout the USA. Bivariate analyses and ordinary least squares regression were used to analyze the data.

The authors find three of Engel’s four supervisory styles and find largely consistent results, with the exception of gender. Further, the authors find strong evidence for persistent agency-level effects.

Supervisory styles are important to consider, especially when trying to effectively control the behavior of subordinates. While this study cannot address the impact of organizational differences, the consistent agency-level effects suggest this as something that should be considered again in future research.

China's remarkable income growth has changed the food landscape in recent years. Chinese consumers are demanding greater food quantity and quality and changing the nutrient content of their diets. Most food demand studies are based on data from earlier time periods before these structural changes had taken hold. The purpose of this paper is to show how the rapid change in food markets and surprisingly slow growth of food imports warrants a new assessment of food demand in China.

Engel equations measuring elasticities of food quantity and quality purchases with respect to household income are estimated. These estimates are then converted to nutrient elasticities to show how the availability of nutrients varies with income based on the Engel demand relationship.

The income elasticities diminish as income rises. Households in the top tier of the income distribution appear to have reached a saturation point in the consumption of most food items. As income rises, most additional spending is on foods with higher unit values that may reflect better cuts of meat or branded items. The pattern of food purchases for households at different income levels suggests that protein, saturated fat, and cholesterol intake rises with increased income. The change in diets prompted by rising income is most pronounced for low‐income households.

This paper applies a unique approach to measure income, quality, and nutrient elasticities within the same framework of Engel relationship. The finding has important implications for opening new market opportunities of imported foods and understanding dietary change in China.

Dominance techniques are used to analyze and rank inequality, welfare, and poverty across regions in Thailand in the 1990s. Inference-based dominance methods are applied to consumption expenditure microdata from the Household Socio-Economic Surveys (SES) of 1992, 1994, 1996, 1998 and 2000. Attention is focused on the period immediately before and after the economic contraction of 1996–1997. Lorenz dominance is employed to assess inequality, while first-order Engel food share dominance is applied to rank welfare across time and among regions. Poverty is evaluated by comparing truncated food-share quantile functions. The evidence reveals that the economic crisis in 1997 seems to affect inequality in Bangkok (the richest region) more than the Northeast (the poorest region), and most dramatic changes occur in the North and South. Welfare in Bangkok is unambiguously higher than in other regions before and after economic contraction. In fact, the great economic contraction changes the rankings of economic well-being and poverty only in the North, South, and Northeast.

This chapter is based on the work of Professor Charles Engel who, sadly, passed away early in 2019. Some 20 years ago, Professor Engel was advocating that higher education should take a lead in remediating global challenges, particularly those of sustainability. He took a broad view of the concept of “sustainability,” based largely on the Brundtland (1987) view of global challenges. Engel proposed that successful approaches to address the complex problems of sustainability should be explored across disciplinary boundaries. The University of Manchester developed a series of course modules focusing on these major challenges, largely run on interdisciplinary lines. Initially the concept was explored across science and engineering, with the support of the Royal Academy of Engineering. Charles Engel, a leading authority on its use, advised using Problem-Based Learning as a means of addressing the wicked problems in interdisciplinary groups. The pilot modules were extensively evaluated and reported. Since then the course units have developed and diversified, with extension to other schools, universities, countries, and to postgraduate courses. This transformative concept has also been explored in hybrid online format. The current chapter will re-introduce some of the original ideas and bring together the many threads that have emerged.

Calculates income elasticities of demand for ten commodity groups and 30 rural regions in China by fitting Engel functions to a set of household expenditure survey data. Finds that staple food, clothing and fuel are necessities, while housing, service, eating out, entertainment and culture, and non‐staple food are luxuries. Discovers substantial variations in the elasticities across regions. Introduces Kmenta’s model to take advantage of the cross‐sectional nature of the data, showing it to dominate the conventional approach.