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The purpose of this paper is to analyze and compare the costs of price and income subsidies when the food security policy targets the urban poor. The result may help policymakers choose a desired subsidy scheme to ensure food security for the urban poor facing food price surge.

The analysis consists of three parts: constructing an empirical model on provincial panel data in 1993‐2009 estimating the impact of grain price on food security among urban residents by different income level; evaluating the potential costs of shifting to income subsidy aiming to maintain the real income levels of the low income, lowest income or the poor residents if grain price increases by 20 percent; and comparing with the cost of price subsidy to achieve the same policy goal.

The paper finds that, food price surge will hurt the urban poor much more seriously than the high income population; the rich residents may receive more benefit from price subsidy; and income subsidy has obviously a cost advantage while the targeted people benefit more.

The obvious value of the paper is to show that income subsidy is much more desired than price subsidy, if the policy goal is to help the poor during food price surge.

This study examines the importance of income income-shifting arrangements of US multinational corporations (MNCs) on future stock price crash risk.

This study employs a sample of 7,641 corporation-year observations over the 2005–2017 period and uses ordinary least squares regression analysis.

The authors find that the income-shifting arrangements of MNCs are positively and significantly associated with stock price crash risk after controlling for corporate tax avoidance and other known determinants of stock price crash risk in the regression model. This result is robust to alternative measures of stock price crash risk and income-shifting, and several endogeneity tests. The authors also observe that income-shifting arrangements increase stock price crash risk both directly and indirectly through the information opacity channel. Finally, in cross-sectional analyses, the authors find that the positive association between income-shifting and stock price crash risk is more pronounced for MNCs that use tax haven subsidiaries and have weak corporate governance mechanisms.

The authors provide new empirical evidence that MNCs will likely face significant capital market consequences regarding their income-shifting arrangements.

The challenge of predicting changes in aggregate income and stock prices is one that has occupied the research agendas of economists. This paper aims to use the consumption–income ratio and the dividend–price ratio to predict future income and stock prices.

To examine the stability of the consumption–income ratio and the dividend–price ratio, the authors run a two-variable, two-lag reduced-form VAR in the vein of Cochrane (1994), using a lag of each respective ratio as exogenous to the VAR. Additionally, the authors estimate an AR(4) model for income and prices.

The consumption–income ratio and the dividend–price ratio remain key to understanding future movements in income and stock prices. The consumption–income ratio significantly predicts future income in the USA, and aggregate income is easier to predict than consumption in the VAR model. The dividend–price ratio does not significantly predict future price growth. Consumption and dividend shocks have lasting impacts on income and prices.

The consumption–income ratio and the dividend–price ratio are still key to understanding future movements in income and stock prices. The consumption–income ratio significantly predicts future income in the USA, and aggregate income is easier to predict than consumption in the VAR model. However, the dividend–price ratio does not significantly predict future price growth, a change from previous research from the 1990s, despite the increasing complexity of stock markets. Consumption and dividend shocks have lasting impacts on income and prices and appear to be significant drivers in both the short- and long-run variance in income and prices.

The purpose of this study is to assess the impact of rising food prices on food demand and nutrient intake among rural–urban migrants and whether such impact varies across income classes.

Using data from the China Health and Nutrition Survey (CHNS), this study adopts a quadratic almost ideal demand system (QUAIDS) for food demand elasticity and an indirect estimation method for nutrient elasticity to investigate the effects of rising food prices on food demand and nutrient intake among rural–urban migrants.

The estimated results indicate that an increase in the price of pork alone would lead to a larger reduction in most nutrients among rural–urban migrants than other single targeted food group, and a simultaneous rise in the price of all food groups would have a remarkably adverse effect on the nutritional status of rural–urban migrants in comparison to the nutritional effects of a rise in one targeted food group. In addition, the nutritional effects of food prices across income classes show that the nutritional status is particularly vulnerable to rising food prices among low-income rural–urban migrants.

This paper focuses on analyzing the impact of rising food prices on the nutritional status of rural–urban migrants, a topic that is very limited in the literature. This study provides a fresh look at the effect of volatile food prices on food demand and nutrient intake among rural–urban migrants. The results indicate that income growth would have a remarkable positive effect on nutrient intake for rural–urban migrants, especially for low-income rural–urban migrants. However, an increment in nutrients due to a growth in income would not be far from enough to cover the reduction in nutrients as a result of a simultaneous rise in price of all the studied food categories at the same rate.

The purpose of this study is to investigate whether increases in homeowner green amenities occurred because of income tax credits to the degree that changes in housing prices are measurable. Are higher incomes, lower mortgage rates and green income-tax credits impacting housing price changes?

The paper uses the least-squares regression model with natural log specifications. The log of income and a dummy variable, which was assigned to the Energy Policy Act (2005) and the American Recovery and Reinvestment Act (2009) coverage dates are used as independent variables. Two regression models were examined using monthly housing price data from January 1990 through the year 2018. The first regression model used a single dummy variable for credits available under the Policy Act of 2005 and the Recovery Act of 2009. The second regression model considered the credits granted under these two laws separately. Disposable income per capita impacts demands for housing while green upgrade expenditures affect the cost of housing.

The laws set low credit limits of $500 followed by $1,500 but because of the multiplier effect, the spending appears to have magnified and been much higher. The credit availability variables have positive coefficients and were significant at 1 per cent. This implies that single-family housing prices were sensitive to the existence of residential energy property income-tax credits. The R² results were 0.93 or above for both models.

The data used was aggregated and publicly available online. Many studies use aggregated macroeconomic data when modeling housing prices using the exogenous variable of disposable income but there is no substitute for examining individual homes by location and their sales price to see under what conditions green income-tax credits have the most impact. There could be demographic issues that are missed when using aggregated information.

Spending on heating/cooling systems, dual pane windows and other green amenities keeps the housing stock modernized and housing prices steady or rising. An additional benefit is that spending motivated by self-interest can simulate household consumption spending. Houses deteriorate due to wear and tear. Physical-repairable depreciation represents a situation where maintenance funds are continuously needing to be spent. Repairs and upgrades to the structure of the property keep its price stable by stopping the physical depreciation that would otherwise occur with the passage of time.

The paper provides support for the idea that residential green amenity upgrades positively impact the value of a house. These green-amenity upgrades, which other research studies have suggested should be included explicitly in the appraisal process, are a major characteristic of a property when a price estimate is being done. Housing being sold should have a section on the information sheet noting the property green upgrades that exist and an energy efficiency score should be assigned to each house listed for sale.

There are few (if any) academic research papers studying the impact of green tax credits available under the Energy Policy Act (2005) and under the American Recovery and Reinvestment Act (2009). The degree to which green income-tax credits stimulate spending on housing has not been addressed by researchers. This paper is an initial research attempt to quantify whether these legislative efforts measurably encouraged homeowners to adopt newer, greener technologies.

Previous studies conducted for developed countries like the United States, Canada, and the United Kingdom have often found charitable giving by individuals to depend on income, the tax price of giving, and other variables. This article makes use of confidential tax file data to conduct a similar study for Singapore, a rapid‐growing newly‐industrializing country. The results indicate that disposable income, the tax price of giving, donor’s age and educational attainment are important determinants of charitable giving by individuals. Donations are found to be income‐inelastic but highly price‐elastic. Thus, lowering the price of giving through tax incentives can be very effective in encouraging private donations to charity.

1. INTRODUCTION The recent proliferation of literature on the problems inherent in inflation, unemployment and incomes policy does not lag far behind the rate of inflation that initially prompted it. Before we get into the discussion of incomes and prices policies, it will be advisable to (a) present some evidence on the wage‐price‐unemployment behaviour in selected industrialised countries and (b) discuss theoretical and empirical results which have led to the conclusion that monetary and fiscal policies will not be adequate to meet the current inflationary problems. The first should provide substance to the claim that inflation has increased over time and has now become a more critical problem; the second should throw some light on the nature of current controversy on inflation and why mixed economies should need to supplement monetary and fiscal policies by other policies to provide themselves with a better trade‐off between inflation and unemployment. Accordingly, we will (1) describe recent wage‐price‐unemployment experience in selected industrialised countries, (2) discuss theoretical and empirical issues involved in the study of wage‐price‐unemployment behaviour, and (3) present the rationale advanced for an incomes policy, and discuss the past experiences of countries which have experimented with incomes policies and conclude with the suggestion that incomes policy and manpower policy be considered as complementary.

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 decompose and measure the microstructure of property investment returns for Tokyo’s residential property markets in as much detail as possible in comparison with office market.

Using enterprise value data for property investment trust companies composed of share prices available on capital markets, this study proposed a method of estimating property investment returns corresponding to changes in capital markets, and clarified the distortion in capitalization rate that are formed based on property appraisal prices.

The results for residential property showed that as building floor space increased, income and price increased while the discount rate decreased. In particular, a higher return could be obtained from office property than residential property by investing in larger-scale properties. Building age lowered asset price and income for both residential and office property, especially for residential property.

In Japan, investors believe that investment returns are high for properties close to the city centre, relatively new properties and those with large design or floor space. Therefore, this study first measured how asset prices, income and asset price–income ratios that comprise property investment returns change based on differences in these property characteristics. Second, the reliability/distortion of information that can be observed on the property investment market was measured. Furthermore, there was a significant divergence between discount rates and risk premiums formed by asset or space markets versus capital markets.

The differences of discount rate and risk premium formed by asset markets versus capital markets indicate that appraisal prices have biases. Thus, when it comes to property investment decisions, it is essential to make active use not just of property investment returns based on appraisal prices formed by asset markets but also information formed by capital markets.

A greater difference was generated in a shrinking market, suggesting that analysing property returns estimated on asset market information alone could lead to erroneous investment decisions.

This research is the first to use the enterprise value data from real estate investment trust companies composed of share prices available on capital markets for calculating discount rate and risk premium in property market.