Narrow Results

Food safety concerns have become increasingly important challenge for agricultural trade. Sanitary and phytosanitary (SPS) measures are often considered as major non-tariff trade barriers, which have surged rapidly over the recent decade. This study systematically investigates the impact of China’s SPS measures on Thai fruit exports. The panel dataset is constructed with 17 Thai fruit items for the sample period 2000–2018. Gravity equations are estimated to quantify the trade effects of SPS measures on the value of fruit exports from Thailand to China. The results from the sectoral analysis reveal that the restrictiveness of SPS measures has a positive and substantial effect on export volumes. This suggests that non-arbitrary and informative SPS requirements imposed by a large importing country would help facilitate the agricultural trade.

This study examines the relationship between global value chain (GVC) participation and workers’ wages and the disparities in wage benefits from GVC participation. It employs a pseudo-panel approach to treat endogeneity biases, utilizing pseudo-panel data constructed from the Thai Labour Force Survey, 1995–2011. The results show that GVC participation, on average, induces higher hourly wages through forward and backward linkages. Although forward linkages inclusively and positively affect workers’ wages, the wage benefits of backward linkages accrue to particular demographic groups. Therefore, government policies must be designed to promote GVC participation, particularly forward linkages, and support disadvantaged demographic groups facing disproportionate wage effects.

The residential sector in Thailand has been a fast-growing energy consumption sector since 1995 at a rate of 6% per year. This sector makes a significant contribution to Thailand’s rising electricity demand especially during the COVID-19 pandemic. This study projects Thailand’s residential electricity consumption characteristics and the factors affecting the growth of electricity consumption using a system dynamics (SD) modeling approach to forecast long-term electricity consumption in Thailand. Furthermore, the COVID-19 pandemic and the lockdown can be seen as a forced social experiment, with the findings demonstrating how to use resources under particular circumstances. Four key factors affecting the electricity demand used in the SD model development include (1) work and study from home, (2) socio-demographic, (3) temperature changing, and (4) rise of GDP. Secondary and primary data, through questionnaire survey method, were used as data input for the model. The simulation results reveal that changing behavior on higher-wattage appliances has huge impacts on overall electricity consumption. The pressure to work and study at home contributes to rises of electricity consumption in the residential sector during and after COVID-19 pandemic. The government and related agencies may use the study results to plan for the electricity supply in the long term.

This study introduced a new approach for monitoring regional development by applying satellite data with machine learning algorithms. Satellite data that represent physical features and environmental factors were obtained by developing a web-based application on the Google Earth Engine platform. Four machine learning methods were applied to the obtained geospatial data to predict provincial gross domestic product. The random forest method achieved the highest predictive performance, with 97.7% accuracy. The constructed random forest model was extended to conduct variable importance and minimal depth analyses, enabling the quantification of a factor’s influence on the prediction outcome. Variable importance and minimal depth analyses generated similar results, indicating that urban area and population are the most influential factors. Moreover, environmental and climate indicators exert medium-level effects. This study showed that integrating available satellite data and machine learning methods could be an alternative framework for facilitating a timely and costless monitoring system of regional development.

In rural areas of developing countries, shocks and financial constraints on households are generally recognized as obstacles to children’s schooling opportunities. This paper investigates the effects of income shocks and borrowing constraints on household demand for education in rural Thailand, using the Townsend Thai panel data spanning from 2013 to 2017. Information on annual rainfall at the provincial level is used to estimate a transitory income component for Thai rural households. Estimation results indicate that income risks and borrowing constraints have a substantial negative impact on child schooling outcomes, including educational attainment and the number of years delayed in school. It also finds that transitory income results in increased household education expenditures conditional on children’s attendance at school. These findings suggest that in addition to households’ socioeconomic status, children’s human capital is at risk mainly due to income uncertainty and the absence of well-developed financial and insurance markets.

Thailand’s aging population has impacted its labor force. This study examines additional health capacity to work (AHCW) with established methods. Data were obtained from the mortality registry as well as national health, aging, labor force, and welfare surveys. Utilizing the Milligan–Wise method, the estimated AHCW for those aged 50–69 was 1.3 years (an 8.7% increase) for males and 1.9 years (17.8%) for females, based on the 2005 employment–mortality relationship. With the Cutler–Meara–Richards-Shubik method, the estimated AHCW for those aged 60–69 in 2015 ranged from 0.9 years (13.6%) to 2.0 years (31.3%) for males and from 1.2 years (23.2%) to 1.5 years (29.6%) for females. We also found that older informal workers in Thailand need to work to maintain their standards of living due to limited retirement benefits. Effective policy measures should be implemented to protect informal workers’ health, prevent pensioners from being impoverished, facilitate a more flexible working environment, and help workers maintain skills and job competencies.

Detailed data on the distribution of human populations are valuable inputs to research and decision making. This study aims at compiling data on population density that are more granular than government-published estimates and assessing different methods and model specifications. As a first step, we combine government-published data with publicly available data like land cover classes, elevation, slope, and nighttime lights, and then apply a random forest approach to estimate population density in the Philippines and Thailand at the 100 meter (m) by 100m level. Second, we use different specifications of random forest and Bayesian model averaging (BMA) techniques to forecast grid-level population density and evaluate their predictive power. The use of a random forest model showed that reasonable forecasts of grid-level population growth rates are achievable. The results of this study contribute to the assessment of methods like random forest and BMA in forecasting population distributions.

Thailand has experienced a decline in income inequality coupled with unimpressive economic growth since the end of the 1997/98 Asian financial crisis. This paper uses the structuralist approach to understand how these concurrent economic phenomena have become deeply intertwined. We argue that this intertwining results from Thailand’s economic structure, manifesting two types of dualism: (i) the dualism of the formal–informal sectors and (ii) the dualism of the dynamic–stagnant sectors. A decline in the informal sector in recent years coincides with a decrease in income inequality. Further, the second type of dualism between the dynamic and stagnant sectors has emerged since 2000. The stagnant sectors’ employment share has grown faster than that of the dynamic sectors, resulting in a slowdown in economic growth and less inequality. The decline of the informal sector and the rise of the stagnant sectors are the primary engines weighing down economic growth and reducing income inequality in Thailand.

In salt farms of Thailand, saline ground water is pumped up and then solar-evaporated to produce salt for commercial purpose. However, when they continue to precipitate salt in the same pools, the product is stained yellow or brown in color. In order to recover only white salt, workers cut trees and create a new pool next to the old one. Due to this practice, year by year, salt-farming area loses vegetation cover and expands barren section of salt damage. In order to understand the changes of in salt grains, salt was collected and measured by PIXE. The result indicates that manganese is clearly responsible for the coloring, and possibly also irons. This information is expected to base the discussion to stop deforestation in the salt-damaged area.

National Institute of Advanced Industrial Science and Technology is working for the Global Alliance to Eliminate Lead Paint (GAELP) of the United Nations Environment Program (UNEP), under the cooperation of Iwate Medical University Cyclotron Center and Nishina Memorial Cyclotron Center of Japan Radioisotope Association. In order to demonstrate how the PIXE is useful to monitor lead in human body, hair samples were collected from local communities and analyzed by the PIXE at the University together with the control of office workers. The analysis showed a clear anomaly of lead for factory workers. It is recommended that the PIXE be added as one of the instruments to assist UNEP's lead and other heavy metal studies.

Water and tailings from lead-mining area in Kanchanaburi, Thailand were analyzed by PIXE to study how serious the alleged pollution was. Eleven water samples were collected in the field and were sealed in the tube after the pH < 2 was attained by ultrapure nitric acid. All of the samples were transported to Nishina Memorial Cyclotron Center of Japan Radioisotope Association and analyzed by its vacuum PIXE. The result showed that the water contains up to 25 ppb Pb with an average value 12 ppb. The value is lower than the environmental norm in Thailand (0.05 mg/L) but higher than that of WHO (10 μg/L = 0.01 mg/L). Tailings contain high amount of lead. Since resumption of mining is being considered to deliver the economic expectation of local people, it should be invested in treatment or containment within storage facilities. Also discharge of treated process water should be regularly monitored by competent agencies.

This article investigates the impact of regional integration on intra-industry trade in manufactures between Thailand and other APEC countries. The study uses pooled cross-sectional and time-series data spanning the period 1980–1999 at a 3-digit Standard International Trade Classification (SITC) level. After accounting for trade imbalance and following Thailand's entry into APEC, intra-industry trade in manufactures between Thailand and countries in Oceania and America decreased, while trade with other Asian countries grew marginally. Results indicate that, in the post APEC era, trade openness stimulated increased intra-industry trade levels with countries in Northeast and Southeast Asia, but decreased trade with countries in America.

Thailand's rapid economic development brought about remarkable wealth and poverty reduction over the past three decades. However, the problem of inequality continues to challenge Thailand's development process. The country has long been known for its concentration of growth in and around Bangkok. Despite that, studies on inequality focusing on geographical dimension have been limited. This paper therefore explores disparities as well as convergence in Gross Provincial Product (GPP)-per-capita over the past two decades. It also investigates growth determinants at provincial level. Finally, the disparities in poverty and the extent to which provincial growth and inequality affect poverty are analyzed.

This study assesses the impact of cash transfers to low-income female Thai students on improving upper secondary school outcomes, as measured by grade point average (GPA) and transition to tertiary education. Utilizing official records from a charity organization providing substantial cash transfers to secondary students and student records from participating schools, we find the transfers have no effect on improving recipients’ GPAs compared to non-recipients. However, the scholarship recipients are 22% more likely to transition to university education than non-recipients and the presence of scholarship recipients in the classroom increases the likelihood of female non-recipients to attend university.

Using unconditional quantile regression and an approach which allows the identification of the individual contributors to the gender wage gap and its over-time change, we study the gender wage differentials over the whole distribution in Thailand from 1991 to 2007. We also propose an extension of the single quantile decomposition to explore the origins of the distributional changes in gender wage differentials over time. A persistent sticky floor effect and declining gender wage gaps over time are observed. Aggregate decompositions using a reweighting approach show that most of the gap and changes in gaps are due to (changing) coefficients effect. Detailed decompositions show that within the (changing) characteristics effect, education contributes to the narrowing of the gap over the whole distribution, and within the coefficients effect age and the constant term are the most influential factors but with opposite effects.

This study investigates technological spillovers of foreign direct investment (FDI) in horizontal, upstream, and downstream industries on domestic manufacturing firms in Thailand, using firm level data from the 2012 industrial census conducted by the National Statistical Office. First, we measure total factor productivity (TFP) and estimate stochastic production frontier to find technical efficiency of firms. Next, we examine impacts of the FDI and other factors on the TFP and technical efficiency of domestic firms. The results provide no evidence on spillover effects of the FDI in horizontal industries on either the TFP or technical efficiency of domestic firms. While the FDI in upstream industries shows negative spillover effects, the FDI in downstream industries reveals positive and significant spillover effects on firms in all industry groups. Firm-specific characteristics such as age, size, availability of imported raw materials, location at industrial estates, and R&D activities all had positive effects on firms’ TFP and technical efficiency in total industries. Although export capability had a positive impact on total factor productivity and technical efficiency of domestic firms in the capital and technology-intensive industries, the effect was insignificant in the labor-intensive ones. The findings imply limited spillover effects of the FDI on domestic firms but highlight favorable effects of the openness policy (affecting availability of imported raw materials and exports), infrastructural investment (available in the industrial estates), and R&D activities. Incentives should be given to the FDI with vertical linkages with domestic input suppliers in order for local firms to gain the most from FDI technology transfers.

This paper applies business cycle accounting methodology to analyze the sources of aggregate fluctuations in Thai economy, especially during the recent severe recessions in 1997–1998 and 2008–2009. This exploration helps researchers uncover possible shocks and frictions that drive business cycle in a small and open economy within a minimal model set-up. Under this methodology, a fluctuation in aggregate output can be accounted for by exogenous time-varying wedges, namely efficiency wedge, investment wedge, labor wedge, government wedge, etc. This study found that the efficiency wedge is essential in accounting for aggregate output, consumption and investment fluctuation, while the bond wedge, which only present in an open economy setting, is a prime factor in accounting for movement in current accounts. I conducted counterfactual experiments to see what accounts for the output drop during recent recessions. I find that the efficiency wedge played a key role in recent recessions in Thailand, while the investment wedge was accounted for slow economic recovery after the recessions.

We investigate the factors that influence adoption of competition law using a panel of countries from 1970 to 2015. We find that in addition to development level, trading arrangements and peer pressure have also influenced adoption. The spread of competition laws adopted from Western precedents left a question regarding the extent they have been tailored to the diverse circumstances of the Association of Southeast Asian Nations countries. We document the nature, structure, conduct and scope of competition laws by comparing and contrasting the experience of the Philippines and Thailand. Our descriptive analysis reveals that the force and influence of the law are not entirely dependent on early adoption.

The countercyclical pattern of saving in Thailand in the 1990s and 2000s raised questions about household saving behaviors in the country. Using constructed pseudo-panel data sets from the Thai Household Socioeconomic Surveys (SESs) from 1992 to 2011, this paper estimates the intensity of the precautionary saving motive, measured by the coefficient of relative prudence of households in Thailand. By using a dynamic pseudo-panel approach to address concerns with regard to individual heterogeneity causing bias in estimation, the estimated relative prudence of Thai households is around 2, which shows a low precautionary saving motive among these households compared to other countries. Estimates based on disaggregation by demographic characteristics show that as a result of the government-assistance policy, older cohorts and those who live in the rural areas show lower prudence.

This paper revisits the causal relationship between education and earnings, or the returns to education, using Thailand’s socio-economic household survey data. We show that, with the minimum modeling assumption, the causal effect of education on earnings can be nonparametrically identified only when there is no unobserved ability affecting both education and earning, and when the selection mechanisms are conditionally independent to earnings conditioning on potential experience and education. The causal effects of education on earnings are estimated using a nonparametric approach with selection bias adjustment and parametric approaches with selection bias and ability bias adjustments. The results show different estimates for returns to education across model specifications, indicating the importance of the bias adjustments and parametric assumptions.