This paper aims to contribute to a better understanding of Thai agriculture, the sector that currently employs about one third of the country’s labor force. We first draw out key stylized facts on our farms, farmers and farming from various granular farmer’s administrative data sets that allow us to observe what has happened at the plot, labor and household levels over the past decade, and cover more than 90% of farmers nationwide. We then use a stochastic frontier analysis to identify key drivers of household’s agricultural productivity, and project the potential productivity impacts from the four key driving factors: climate change, aging, irrigation and technology for every tambon nationwide. A meta-analysis is then used to illustrate the landscape of technological development throughout the rice value chain in Thailand. Finally, we use lab in the field experiments to understand behavioral insights that underly farmer’s incentives particularly in the context of technological adoption. Our results shed some lights on how to design, prioritize and implement policies to ensure that our farmers stay competitive, resilient and sustainable.

We study the dual role of networks in providing insurance and in propagating idiosyncratic shocks by using variation in the timing of severe shocks on health spending experienced by households in Thai villages. We find no impacts on food consumption. Smoothing is largely achieved through local gift and loan networks. However, insurance is partial for some households so they adjust their production decisions-drawing on their working capital, cutting input spending, and reducing labor hiring, hence propagating the shocks to other households. Wefind that upstream businesses close to the underinsured households in the supply chain network experience reduced local sales and increased inventories. Likewise, workers closer to the underinsured households in the labor network experience declined probability of working locally and reduced earnings. We find evidence of ex-post adjustments of these upstream households through shifting resources towards activities with lower exposure to local shocks. Our results suggest that social (village-level) gains of expanding health insurance might be higher than private (household-level) gains.

This study analyzes the entire universe of registered firms in Thailand. There are five main findings. First, firm size distribution is smooth, with a majority of firms in the middle of the distribution; the apparent ”missing middle” phenomenon is entirely driven by arbitrary categorization of small and medium enterprises (SMEs). Second, the Thai corporate sector is very concentrated; the concentration has also risen over the past decade. Third, larger firms seem to have advantages over smaller firms regarding financing. Fourth, smaller firms tend to disproportionately invest less in fixed assets than larger firms. Finally, firms in the middle of the size distribution exhibit the highest return on asset (ROA) but have low leverage, consistent with the symptom of credit constraints. Large firms, in contrast, seem to have lower ROA but higher debt. Meanwhile, smaller firms seem to have both lower leverage and ROA. Overall, our results suggest that the Thai corporate sector exhibits both inefficient capital allocation and financial vulnerability. The paper has important policy implications on resource allocation in the economy, particularly, regarding appropriate assistance provided to small and medium enterprises.

This paper uses firm-level data from developing countries to examine the significance of tax-motivated profit shifting from high-tax to low-tax countries by multinational enterprises and to analyze the extent to which anti-avoidance measures mitigate the profit shifting. Focusing on firms in ASEAN5, this study shows that (1) tax-motivated profit shifting is statistically and economically significant, especially for manufacturing firms, (2) auditing and transfer-pricing scrutiny is more effective in reducing profit shifting than documentation requirement alone, and (3) tax-motivated profit shifting is prominent for large firms, while anti-tax avoidance measures result in the absence of profit shifting detected from small manufacturing firms. The findings have important policy implications regarding tax revenues in developing countries, especially those depending on multinational enterprises but having weak governance.

This paper investigates the impact of exposure to a family business and participating in a family business on individuals decision to start a business (self-employed and small business) and their likelihood of survival. We find that individuals who have a family member doing business are more likely to start their own business. However, only individuals who have actually worked in the family-owned business are more likely to survive longer. This paper demonstrates that the higher the number of hours they worked in a family business, the higher the probability of survival. The impact remains significant even if the sample includes only individuals who are the spouses of business owners. The impact of prior experience from helping a family business depreciates over a short period of time. This result suggests that entrepreneurial skills can be learnt from an apprenticeship in small businesses.

This paper conducts in-depth profiling of players and interlinkages in the Thai financial system based on sectoral balance sheet data and disaggregated supervisory data on banks and mutual funds. Several aspects of Thailand’s financial landscape have been documented. We find that financial interconnectedness has risen and become more complex, with the financial landscape increasingly tilted toward non-bank intermediaries. Network topology suggests a segmented landscape, with the presence of a core cluster where key players including households, firms, large domestic banks, and mutual funds of large banks’ asset management arms are located, indicating their tight interconnections. Leveraging on entity-level balance sheet profiles, we develop a stress-testing framework that is based on a network model of financial contagion. Two types of shocks are studied. For industry shocks, we find that losses generally propagate via the liability and ownership channel and the reverse liquidity channel. But when the losses are large enough, the fire-sale effects dominate. For bank reputational shocks, we simulate a loss of confidence in major banks via deposit withdrawal and fund redemption. While the overall losses are much smaller than those of industry shocks, these risks cannot be ignored since the mutual fund industry stands to suffer and panic selling could amplify the losses.

Information about mutual funds’ stock holdings can provide useful signal for investors. In this study, we show that portfolio of stocks that are not favored by mutual funds tend to perform poorly, with monthly returns of 0.38% to 0.82% lower than stocks more widely held. When compared against asset pricing models, portfolio of such stocks can have monthly alphas as low as -0.33%, and the reason seems unrelated to stock-picking ability. One possible explanation is that demand from institutional investors can drive up stock prices, highlighting the importance of investor clientele in emerging market asset pricing.

One of the proposed explanations for the low-beta anomaly – a prevalent yet puzzling empirical finding that stocks with low systematic risk tend to earn higher returns than the Capital Asset Pricing Model (CAPM) predicts and vice versa – is that leveraged-constrained and index-benchmarked mutual funds drive up demand for high-beta stocks, leading to systematic mispricing. We find evidence that Thai mutual fund managers, on average, favor high-beta stocks and tend to alter their portfolio composition of high-beta stocks in response to fund flows. In addition, funds that hold high-beta stocks perform poorly compared to their peers: a one standard deviation increase in high-beta stock holdings is associated with a 1.3 percentage point decrease in future relative returns.

This study examines the impact of planned obsolescence – the introduction of new models to make existing models obsolete – on secondary markets for mobile phones. Using data of over 320,000 used iPhones listings on Thailand’s largest online marketplace, we document that iPhone prices decrease with age, around 2.8 to 3.2 percent for each passing month. We find no evidence that the price decline accelerates after launches of new models (i.e. obsolescence), lending support to the view that consumer in durable goods markets are rational and forward-looking.