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This study simultaneously explores the nexus among formal, semiformal and informal credit markets and farm households' credit demand determinants in Vietnam.

This study uses a multistage stratified random sampling process for a survey of 648 smallholder farmers in the Red River Delta (RRD), Vietnam. The trivariate probit model (TVPM) is used to address the interdependence of farm households' credit demands in different credit markets.

The results reveal complementary relationships among two pairs of credit markets (formal versus informal and semiformal versus informal). There are dissimilarities among the determinants (household characteristics, household head's characteristics, credit history and geographic factors) of farm households' credit demands in different markets, reflecting segmentation of Vietnam credit markets.

The study's empirical findings are important for policymakers and credit providers to enhance farm households' access to credit for agriculture and to improve the operations of the three credit markets.

This is the first empirical study in Vietnam and one of few in other developing countries simultaneously exploring the determinants of credit demand in and interrelationships among all three credit markets to provide more comprehensive and accurate results.

The purpose of this paper is to evaluate the effects of price and income changes on food and nutrient demand of rural households by including own-produced food and production-side effects in the demand estimation to correct potential measurement bias in the income and price elasticities for rural households in underdeveloped areas. Simulation results of income and grain price changes on food and nutrition security are provided for economic nutrition security policy applications.

This study analyzes survey data of 1,555 households from underdeveloped rural areas of China to find out how price and income changes affect food and nutrition insecurity of rural households. The authors employ the quadratic almost ideal demand system (QUAIDS) in a two-stage budgeting framework, using quality adjusted prices that were retrieved with regressions of the difference between the unit value surveyed at household level and its village average on household characteristics. The bias correction is implemented by using an augmented IV (instrumental variable) method, in which each market price is instrumented with farm-specific variables. Important macro- and micronutrient elasticities are computed for (a) households with agriculture as main income and (b) other households (of which still many have agriculture as a side business). Finally, the authors use these elasticities to simulate how changes in income or grain prices affect the food and nutrition security in the studied areas.

In general, food income elasticities of agricultural households are at a higher level than those for other households, and so are the food price elasticities. Income changes also have a greater nutritional effect on agricultural households than on other households. Nutrient income elasticities ranged from 0.22 (energy) to 0.27 (Vitamin A) for agricultural households and from 0.19 (energy) to 0.23 (Vitamin A) for other households. Grain price increases have greater effect on nutritional status of non-agricultural households, while a grain price reduction is not clearly favoring the nutritional situation of a particular household group.

This demand study contributes to the literature by taking into account differences in consumption of own production between households and the potential endogeneity of prices resulting thereof. The authors also demonstrate that merely reporting nutrient elasticities might not be sufficient for policy recommendations, and simulations should be reported as a valuable addition.

Homeownership has been the main focus of housing policies in most countries. Typical means that households use to achieve homeownership is to take out a loan and supplement this with accumulated wealth for a downpayment. This paper aims to analyze the mortgage demand behavior of households in the UK, Australia and Japan.

Using three panel data sets, HILDA for Australia, KHPS for Japan and USS for the UK, the paper estimates three equations using ordinary least squares: mortgage demand function, housing demand function and initial loan to value ratio function.

Though homeownership is a preferred tenure and the mortgages are “recourse” loans, housing markets in these three countries operate in different mortgage market institutional structures. Results indicate that income elasticity of mortgage demand differ despite income elasticity of housing demand being similar. Different mortgage institutions in countries that pose constraints for borrowers also determine mortgage demand. Other factors such as demography and economic conditions have also played an important role in determining mortgage and housing demand.

The paper is first, to the authors’ knowledge, that explores the role of institutions in mortgage demand in a comparative framework for the UK, Japan and Australia.

The main objective of this paper is to analyze patterns of consumption expenditure and the effects of income, prices and socioeconomic and demographic factors on demand among elderly- and young-adult-headed households in Brazil.

The authors estimated a Quadratic Almost Ideal Demand System demand system using the main household consumption good groups – food, housing, clothing, transportation, health care and other expenses – with data from three Brazilian Household Budget surveys.

The study results showed that elderly- and young-adult-headed households have different consumption patterns. The consumption of food, transportation and health care was more price-sensitive for households headed by the elderly, while higher income increases health care expenses in elderly-headed households to a greater extent than it does in younger-headed households.

The limitations are due to the structure of the data used, such as the effects of seasonality and individualized demand analyses, and sample design in the estimates. However, due to the structure of the demand models, which when estimating by seemingly unrelated regressions do not allow to take into account the sample design.

As a consequence of population aging, the Brazilian economy will experience changes in the composition of household consumption, mainly for food, housing, transportation and health-care-related products.

This paper fulfills the lack of studies that analyze the consumption patterns and how demand varies across different types of elderly-headed households in a developing country, such as Brazil.

Some of the major concerns since the implementation of smart meters (prepaid meters) in some parts of Ghana is how electricity consumers have benefited from data obtained from these meters by providing important statistics on electricity-saving advice; this is one of the key demand-side management methods for achieving load reduction in residential homes. Appliance shifting techniques have proved to be an effective demand response strategy in load reduction. The purpose of this paper is therefore to help consumers of electricity understand when and how they can shift some appliances from peak to off-peak and vice versa.

The research uses an analysis technique of Richardson et al. (2010). In their survey on time-of-use surveys to determine the usage of electricity in households as far as appliance shifting was concerned, this study allowed for the assessment of how the occupants’ daily activities in households affect residential electricity consumption. Fell et al. (2014) modeled an aggregate of electricity demand using different appliances (n) in the household. The data for the peak time used in this study were identified from 05:00 to 08:00 and 17:00 to 21:00 for testing the load shifting algorithms, and the off-peak times were pecked from 10:00 to 16:00 and 23:00. This study technique used load management considering real-time scheduling for peak levels in the selected homes. The household devices are modeled in terms of controlled parameters. Using this study’s time-triggered loads on refrigerators and air conditioning systems, the findings suggested that peak loads can be reduced to 45% as a means of maintaining the simultaneous quality of service. To minimize peak loads to around 35% or more, Chaiwongsa and Wongwises (2020) have indicated that room air conditioning and refrigerator loads are simpler to move compared to other household appliances such as cooking appliances. Yet in conclusion, this study made a strong case that a decrease in household peak demand for electricity is primarily contingent on improvements in human behavior.

This study has shown that appliance load shifting is a very good way of reducing electrical consumption in residential homes. The comparative performance shows a moderate reduction of 1% in load as was found in the work done by Laicaine (2014). The results, however, indicate that load shifting to a large extent can be achieved by consumer behavioral change. The main response to this study is to advise policymakers in Ghana to develop the appropriate demand response and consumer education towards the general reduction in electrical load in domestic households. The difficulty, however, is how to get the attention of consumer’s on how to start using appliances with less load at peak and also shift some appliances from off-peak times. By increasing consumer knowledge and participation in demand response, it is possible to achieve more efficiency and flexibility in load reduction. The findings were benchmarked with existing comparison studies but may benefit from the potential production of structured references. However, the findings show that load shifting can only be done by modifying consumer actions.

It should be remembered that this study showed that the use of appliances shifting in residential homes results in load reduction benefits for customers, expressed as savings in electricity prices. The next step will be to build on this cost/benefit study to explain and measure how these reductions transform into net consumer gains for all Ghanaian households.

Load shifting will include load controllers in the future, which would automatically handle electricity consumption from various appliances in the home. Based on the device and user needs, the controllers can prioritize loads and appliance usage. The algorithms that underpin automatic load controllers will include knowledge about the behaviors of groups of end users. The results on the time dependency of activities may theoretically inform the algorithms of automatic demand controllers.

This paper addresses an important need for the country in the midst of finding solutions to an unending energy crisis. This paper presents demand response to the Ghanaian electricity consumer as a means to help in the reduction of load in residential homes. This is a novel research as no one has at yet carried out any research in this direction in Ghana. This paper has some new information to offer in the field of demand in household electricity consumption.

This paper aims to understand housing demand of urban Indian households in terms of housing and household-level characteristics. Because a house is a bundle of certain characteristics which vary across houses, each characteristic has an implicit price. Finding this implicit price for certain important characteristics is the first objective of this study. The second objective of the paper is to compute the income elasticity and price elasticity of housing demand for these cities.

To achieve comparable estimates, household-level data from India’s National Sample Survey Organisation housing surveys for the years 2002 and 2008-2009 have been used. A hedonic price function is estimated using ordinary least squares (OLS) and Box-Cox functional forms to estimate the implicit prices of housing characteristics. This exercise is attempted for owned and rented houses separately. Demand function required for computing the elasticities, uses the hedonic price index derived from the implicit prices and household characteristics.

The study finds housing demand to be income elastic and price inelastic for the six cities across both the time periods.

Firstly, this study includes housing characteristics such as individual access to drinking water, modern sanitation facility, separate kitchen, condition of the structure, existence of a road with street light and whether the house is in a slum or non-slum area in the hedonic price function. These variables were not used in any of the earlier studies pertaining to India. Secondly, it uses the Box-Cox non-linear form to derive the hedonic price function, a specification not used earlier. Thirdly, this is the first study analysing housing demand across the six largest Indian cities.

The purpose of this paper is to investigate antecedents of households' local demand for domestic tourism in Jordan.

A sample of 600 households is surveyed and a two‐stage demand model is estimated. Stage 1 identifies the antecedents of the probability of entering the domestic tourism market. Stage 2 identifies the antecedents of households' expenditures on domestic tourism. The Heckit method is used to estimate the first stage and the OLS is used to estimate the second stage.

Certain socio‐economic factors (household characteristics, individual characteristics and ability variables) impact the local demand for domestic tourism, as do price and income variables.

The generalizability of results to other countries is limited.

Identification of antecedents of local demand for domestic tourism helps governments to formulate and modify future tourism strategies.

This paper contributes to the literature by including socio‐economic variables in the domestic tourism demand model. Further, there is a dearth of studies in Jordan in general and regarding domestic tourism in particular.

This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households.

A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding.

Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R² > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects.

This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums.

All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas.

This paper uses primary survey data (collected by the authors) to assess housing affordability for the urban poor of Lucknow city. It makes the results of the study credible and useful for further applications.

This paper aims to examine the compatibility of Giffen behaviour with residential demand for kerosene and cooking gas.

In total, 600 questionnaires were administered on selected households in Ondo State while 485 were retrieved. Both ordinary least square and instrumental variables (IVs) were estimated, while, the IV estimated result was preferred.

The result showed that Giffen behaviour is compatible with the demand for kerosene in Ondo State, but not for cooking gas. As regard to other factors, prices of the alternatives to kerosene and cooking gas have positive but insignificant impact on the demand for the respective products. Age of the household has a positive significant impact on the demand for kerosene and cooking gas. Household in which the heads has tertiary education demand for kerosene and cooking gas more than those without any form of education. Larger households consume more of both commodities than smaller households.

Based on these findings, the authors recommend that government should continue to subsidize either the production or consumption of household kerosene.

Consumers should not mind the initial expenditure in purchasing cylinder for cooking gas as subsequent expenditure would be lower than that of kerosene.

Regulators should brace to ensure that kerosene and cooking gas be made available at government-regulated prices, particularly by checkmating the activities of the “black-marketers.”

Two outstanding knowledge gaps that this paper filled are in the novelty of this paper regarding the application of Giffen behaviour to kerosene and cooking gas. Second, previous studies did not account for the potential endogeneity problem that is inherent in the joint demand for kerosene and cooking gas. This paper took care of this by estimating the model using IVs.

The purpose of this paper is to investigate household financial choice and the determinants of financial services in rural and urban households in Ghana.

Data from the Ghana Living Standard Survey 5 (GLSS 5) are used to estimate the participation of a household in a particular financial sector and what determines this choice.

The results from Tobit and conditional logit models account for households' demographic characteristics and their financial decisions. The Tobit estimates show that household size, age, sex, marital status, occupation, income, remittances and shocks determine households' participation in the financial markets. Conditional logit model results suggest that locational characteristics are important in obtaining financial services from particular sectors of the financial market. The results also suggest that when the alternatives of financial services are available, rural households are more likely than urban households to obtain their financial services from the informal financial sector.

This current study contributes to the existing literature from the Ghanaian perspective.