ชั้น 2 ธนาคารแห่งประเทศไทย
Understanding the Dynamic of Digital Economy in the Context of Digital Literacy of Thai Households
Digital economy has led to new business opportunities and growth potential especially for developing countries such as Thailand. However, one crucial factor that could create challenges is the readiness of households in adapting to the digital environment. This research proposes that digital literacy of households is the key indicator that helps policy makers to understand the digital divide situation. Digital literacy should be measured by 4 sub-dimensions, namely, 1) the access to digital technologies 2) the level of digital skills 3) the level of digital knowledge and 4) the digital information awareness. After using the principal component analysis (PCA) to develop the scoring system of digital literacy and using the cluster analysis to classify the sample into 3 levels of digital literacy, it is found that households in the illiterate group are mostly unemployed or work in the labor-intensive sector. When looking at how they use financial services, they appear to significantly use fewer banking services and have lower preference on the personalization of services than the digital fluency group. This evidence suggests that populations in the digital illiterate group may have already suffered from the digital divide which could intensify the problem of wealth inequality in the digital era. Consequently, policies that guarantee all households to have certain levels of digital literacy are needed.
Tax Incentives to Appear Small: Evidence from Thai Firms and Corporate Groups
This paper studies the effects of SME tax incentives on firm behaviors. We use firm-level panel data of all registered firms in Thailand to analyze the effects of a large reduction in corporate income tax rates for SMEs in 2011. First, we find that firms responded strongly to the SME tax incentive as indicated by a sharp bunching of firms just below the threshold after the incentive was introduced. The responses were concentrated among firms with positive EBIT, implying a financial motive for firms to remain small. Second, the bunching was prominent for stand-alone firms, where we observe slower revenue growth for those below the threshold. Third, we do not observe bunching for corporate-group firms, but we find evidence of tax-motivated profit shifting among them instead, especially among firms in small groups with weak corporate governance. Our analysis suggests that transfer pricing was likely a primary channel. Finally, despite the unintended consequences, we find that the incentive significantly raised the probability of firm’s survival and encouraged new firm registration, as the policy intended.
Understanding a Less Developed Labor Market through the Lens of Social Security Data
While understanding labor market dynamics is crucial for designing the country’s social protection programs, prohibitive longitudinal surveys are rarely available in less developed countries. We illustrate that employment history from Social Security records can provide several important insights by using data from a middle-income country, Thailand. First, in contrary to the traditional view, we find that the formal and informal sectors are quite connected. Our analysis of millions of individual histories by a machine learning technique shows that more than half of registered workers left the formal sector either seasonally or permanently long before their retirement age. This finding raises a question of whether the social protection schemes being separately designed for formal and informal workers are effective. Second, the semi-formal workers also had a much flatter wage-age profile compared to those always staying in the formal sector. This observation calls for effective redistributive tools to prevent earnings inequality to translate into disparities in old-age and transmit to the next generation. Lastly, on the employer size, we find that almost half of formally registered firms had fewer than five employees, the benchmark often used to define informal firms. This result suggests that the distributions of firm sizes differ across countries and the employer size alone is unlikely sufficient to define informal workers.