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This study aims to apply a proposed methodology for calculating spatial prices in a heterogeneous country setting such as India with limited price information. Based on the empirical evidence, the study plans to draw the spatial price map of India with different colours denoting states and districts with varying level of spatial prices.

This study shows that a procedure proposed by Lewbel (1989), based on the idea by Barten (1964) that household composition changes have “quasi-price effects”, can be used to estimate spatial prices in the absence of information on regional prices.

The evidence on spatial price differences in India, which is the most comprehensive to date because it goes down to district level, shows that the proposed procedure has considerable potential in future applications on other data sets with limited price information. The policy importance of the results is underlined by the sensitivity of the demand elasticities to the inclusion/omission of spatial price variation.

The study uses “pseudo unit values” based on household composition and demographic effects on demand as proxy for the missing price information. While the work of Atella et al. (2004) suggests that such proxies are accurate representations of true prices, nevertheless, they are proxies and the results should be treated with caution.

The evidence on spatial prices in India that point to a high degree of price heterogeneity between regions implies that welfare applications such as income distributional and poverty studies must take account of the price heterogeneity within the country. The implications extend beyond India to cross-country exercises such as the purchasing power parity calculations undertaken by the International Comparison Project.

This is one of the first studies that provide evidence on spatial price heterogeneity within a country without requiring regional price information. Methodologically, the paper builds on the suggestion of Lewbel (RES, 1989) in showing how the demographic effects on household expenditure pattern can be used to estimate spatial prices. The value of the contribution lies in the use that the estimated spatial prices can be put to in calculating inequality and poverty rates and in standard of living comparisons between regions in the country.

The objective of this research is to examine, validate, and recommend techniques for handling the problem of missingness in observational data. We use a rich observational data set, the Nielsen HomeScan data set, which allows us to effectively combine elements from simulated data sets: large numbers of observations, large number of data sets and variables, allowing elements of “design” that typically come with simulated data, and its observational nature. We created random 20% and 50% uniform missingness in our data sets and employed several widely used methods of single imputation, such as mean, regression, and stochastic regression imputations, and multiple imputation methods to fill in the data gaps. We compared these methods by measuring the error of predicting the missing values and the parameter estimates from the subsequent regression analysis using the imputed values. We also compared coverage or the percentages of intervals that covered the true parameter in both cases. Based on our results, the method of single regression or conditional mean imputation provided the best predictions of the missing price values with 28.34 and 28.59 mean absolute percent errors in 20% and 50% missingness settings, respectively. The imputation from conditional distribution method had the best rate of coverage. The parameter estimates based on data sets imputed by conditional mean method were consistently unbiased and had the smallest standard deviations. The multiple imputation methods had the best coverage of both the parameter estimates and predictions of the dependent variable.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.

This paper aims to use the approach based on the application of the law of gravity for the study of the flows of export and the effects of the RTAs.

In this paper, the authors evaluate the effects of RTAs on exports between members and non-members taking into account the Vinerian specification. The authors also try to estimate the impact of the recent economic crisis on the flows of export and the success of the RTAs. The authors use a model of static and dynamic gravity for 40 countries and six RTAs during the period 1980-2011.

Definitely the proliferation of RTAs will continue to be one of the driving forces that will constitute the political system and the global economy in the following years. It indicates a process that implies the merger of economies separated in bigger regions of free trade. Regional integration is seen as beneficial in many senses and is the major economic objectives in addition to presenting a stabilizing factor in international relations.

The gravity model is estimated using the last techniques of panel data which takes into account the endogeneity of the effects of integration and the existence of dynamic effect.

This paper aims to investigate a fundamental research question of whether the Islamic banking business model makes corporate earnings more uncertain. This question arises because prior research shows that Islamic banks do well in loan performance but incur more operational costs than conventional banks, indicating the systemic limitation of Islamic banks in business risk management.

The study used a sample of banks to conduct the panel regression analysis with 15 years of data for 532 banks (129 Islamic and 403 conventional) from 23 Muslim countries across the world. The authors estimate earnings uncertainty in two ways: the spread and standard deviation of the country-adjusted return over the sample period and applied the difference-in-difference approach interacting cost to income ratio with the Islamic bank dummy, checking if Islamic bank’s high operational costs contribute to more earning uncertainty.

Islamic banks’ returns on assets are significantly more uncertain than conventional banks due to higher operational costs. Consistent with earlier evidence, the study also finds that Islamic banks generally have fewer nonperforming loans than conventional banks. The authors conclude that Islamic banks trade-off between reducing credit risk and escalating business risk.

This study documents that the Islamic banking model helps build a safer asset portfolio but gives rise to the uncertainty of corporate earnings. Therefore, the choice between Islamic and conventional banking models involves a trade-off between credit and business risks. It is a new finding that we add to the literature body on Islamic finance.

The purpose of this paper is to examine the effect of bank consolidation and foreign ownership on bank risk taking in the Egyptian banking sector.

Following prior studies (e.g. Yeyati and Micco, 2007; Barry et al., 2011), this study uses pooled Ordinary Least Squares regression models under two main analyses to test the relation between concentration and foreign ownership on one hand and bank risk-taking behavior on the other hand, where observations are pooled across banks and years for the 2000-2011 period. The reform plan was launched in 2004 and resulted in various restructuring activities in the banking system. Thus, to control for the effect of implementing the financial sector reform plan on bank insolvency and credit risk, this study includes a reform dummy variable (RFM) for the post-reform period in models testing the association between consolidation, foreign ownership and bank risk. Therefore, this categorical variable identifies whether bank risk is related to the reform activities that have been observed during the post-restructuring period, 2005-2011. Moreover, to accommodate the possibility that effects of bank concentration and foreign ownership on bank risk differ due to the implementation of the reform plan, the author create two interaction terms: one uses the product of the reform dummy variable and concentration measures, while the other uses the product of the reform dummy and foreign ownership variables to capture interactions. These interaction terms and the dummy variable provide ample room to capture the effect of bank concentration and foreign ownership on bank risks during the post-reform period.

This study provides empirical evidence that bank concentration is associated with low insolvency risk and credit risk as measured by loan loss provisions (LLP) in the post-reform period. These results are consistent with the “concentration-stability” view, suggesting that concentration of the banking sector will enhance stability. Moreover, evidence shows that while a higher presence of foreign banks reduces bank credit risk in the post-reform period, it appears to increase insolvency risk. These results are robust to using alternative measures. These findings imply that regulators in emerging countries should support foreign investments in banks to transfer better managerial skills and systems. However, government-owned banks are found to be more prone to insolvency and credit risks; thus, their ownership should not be encouraged. Finally, policy makers should reinforce bank consolidation, be prudent in determining the capital adequacy ratio (CAR) and monitor intensively less profitable, well-capitalized and small-sized banks.

Consolidation of the banking sector decreases insolvency risk and credit risk, as measured by LLP in the post-reform period. This study proposes that bank supervisors implement prudent polices in determining the bank CAR, and monitor intensively less profitable, well-capitalized and smaller banks, as they have incentives to increase risk. In addition, regulators should encourage foreign investment in the banking sector and facilitate their operations in Egypt.

Bank supervisors should intensely monitor banks with high-CARs that exceed mandatory requirements because they may be more likely to engage in more risk-taking activities.

It provides empirical evidence from a country-specific, emerging market perspective, in which restructuring events affect the national economy. Egypt, similar to other emerging countries in Africa, pursues an institutionally based (bank-based) system of corporate governance, where banks are the primary sources of finance for firms. Therefore, restructuring banks and other financial institutions and supervising their operations ensure the soundness and stability of these institutions, which represent the nerve of emerging economies. Because emerging countries tend to share common characteristics and economic conditions, and the reform of their financial systems is significant for economic development, the Egyptian banking reform and restructuring program should be of interest to other emerging countries to capitalize on this experiment. While international studies on these relationships are mostly cross-country or focus on US banks, firm-specific studies are scant. Furthermore, the findings of this study should be of interest to Egyptian regulators, bank supervisors and policy makers studying the implications of bank reforms.

The purpose of this paper is to quantify the value of brands and countries of origin in monetary units. The automobile industry in Thailand is chosen because of the variety of brands and the intense competition within the industry. Both the pick up truck and passenger car market shares have been dominated by Japanese brands for decades, whilst the luxury market has been dominated by German brands.

The data are collected from an authors' survey carried out during the “Thailand International Motor Expo 2007”. A total of 244 models are chosen from 20 brands, and from 7 countries of origin. The hedonic price model is applied to ascertain the price premiums of these different brands, taking into account their countries of origin, since each automobile brand offers several models with distinguishably different features.

The results indicate that different brand names affect consumers' “Willingness to Pay,” in which Mercedes, BMW, and Audi brands are ranked the highest. Surprisingly, Subaru, Mitsubishi and Toyota are the only Japanese brands to have significant brand values. The findings also illustrate a direct relationship between market acceptance and the price premium for automobiles in the luxury car segment, however the same relationship does not hold true for the cars in economy car segment. It seems that Thai consumers put the highest value on cars from Germany, whilst cars from Japan and the USA possess approximately the same value. Korean and Malaysian cars, which focus on low‐prices as a means to obtain a competitive advantage, are as to be expected ranked last. An association was found between countries' GDP per capita and the price premium. Countries with a lower GDP per capita show lower price premiums and vise versa. The exception is Germany, which has a low GDP per capita yet has a higher price premium than the better ranked GDP countries such as the USA

Though the German brands are ranked the highest, competition in the car industry is likely to be intense, since their premiums are not noticeably different. Additionally, there are implications regarding entry barriers for new automobile brands from the same or different countries. These entry barriers are considered to be quite high, as the brand premiums could represent more than 25 percent of the car prices, at least for the compact car segment. A strategy of discounted price penetration is therefore recommended for a brand which is new to the market, and which does not originate from a highly regarded country. For existing brands with below average values, a customer‐based approach is recommended in which those brands improve the attributes in order to create higher premiums.

In addition to confirming the relationship between the price premiums of brands and their countries of origin, this paper successfully provides valuations in monetary units and rankings accordingly. This research could be useful to both incumbents and new entrants, when designing their pricing strategies.

Based on the American antidumping cases against China, the purpose of this paper is to construct an early warning model for Chinese exports.

In order to overcome the drawbacks of the existing early warning models for antidumping, first, the authors screen out six most relevant indices that play a key role in US textile corporations' decision of antidumping petition against China from 2002 to 2006, then design a early warning system for antidumping petition based on panel data logit model.

The regression result indicates that unemployment ratio and import‐penetration ratio significantly influence the antidumping filing decisions; when the other invariables keep the same, with the market share of China textile goods increasing by 1 per cent point, the odds ratio of antidumping petitions against China textiles increases by about 3.7 per cent.

As far as the authors are aware there is no definite research yet about early warning system of antidumping events, and this paper aims to specifically address this issue.

We investigate the relationship between job complexity and skill development of adult workers in Europe using the Cedefop European Skills and Jobs Survey. ¹ The results suggest that challenging workplaces in which jobs are designed to include complex tasks that place high demands on workers’ skills also stimulate skill development. Increasing the degree of job complexity has positive and robust effects on the degree of skill development. Skill development is also positively linked to job tenure. The analysis stresses the importance of on-the-job learning and contextual workplace characteristics for adult workers’ skill development.