Bibliographic record
Abstract
Recent decades have witnessed an unparalleled increase in the globalization of goods markets and financial markets. Technological progress, a decrease in transportation costs, trade liberalization and better investment protection have all fueled international trade integration. This current surge in international trade integration is characterized by a rise of global value chains. Multinational corporations increasingly establish foreign subsidiaries and offshore certain production stages in order to take advantage of lower wages. Developing economies gain from the participation in global value chains by finding access to more sophisticated manufacturing processes and novel technology. Governments therefore attempt to raise foreign investment and global value chain participation of domestic firms by ratifying investment treaties that protect against expropriation. The ratification of these international treaties and the removal of capital controls have also substantially increased global financial integration in the last thirty years. While theory predicts international asset trade to be welfare improving, the surge in the globalization of financial markets has been accompanied by a high frequency of currency crises. Against this background, governments are confronted with the question: How can they reap benefits from the current globalization wave while simultaneously mitigating its negative side effects? I want to contribute to this debate along two lines: First, I investigate the role of currency mismatches in exchange rate crises. Second, I analyze the effects of an increase in perceived expropriation risk in a host country of investment on financial markets and trade in value added. Chapter two deals with the question whether currency crises reduce stock market returns of firms in industrial countries and emerging markets. Moreover, in this chapter I investigate whether these effects are particularly pronounced if countries and companies hold large amounts of net liabilities. Since the Asian Crisis took place in the mid-1990s the literature evaluated whether the existence of foreign currency debt may make nominal depreciations contractionary. The idea is that a depreciation increases the local currency value of a company’s foreign currency debt and diminishes entrepreneurial net worth (”balance-sheet effect”). While the existing literature mainly focuses on long-term effects of depreciations on investment and stock markets, my chapter takes on a different perspective. I initially estimate short-term stock market reactions of individual firms to 85 clearly defined currency crisis events. Subsequently, any variation in these returns within and across countries is explained by the economy’s quantitative foreign currency exposure and the firm’s level of net liabilities. My data includes more than 10,800 companies from 37 countries over the period 1993 to 2011. I find that large devaluation events negatively affect stock markets. Hence, the results suggest that nominal depreciations are on balance contractionary. I also show that companies in countries with larger net foreign currency liabilities as a share of GDP perform worse. Finally, my findings suggest that also the level of a firm’s own debt is an important factor in explaining stock market reactions. To conclude, in chapter two, I provide empirical evidence that both the macroeconomic and microeconomic dimensions to net liabilities matter in currency crashes. Chapter three takes a closer look at the value of investor-state dispute settlement-provisions (ISDS-provisions). This article is joint work with Christoph Moser and Gabriele Spilker. To attract larger investment inflows, countries have increasingly signed investment treaties and free trade agreements that include clauses allowing for investor-state dispute settlements. International investors can sue governments in case of alleged direct or indirect expropriation. While this mechanism is sharply criticized by many actors in global governance, little is known how investors actually value ISDS-provisions. This paper aims to fill this gap. Our preferred empirical strategy exploits an ideal setting for an event study: The sudden and surprising news about a potential executive order by U.S. President Trump to withdraw from NAFTA, implying the loss of ISDS-provisions for U.S.-investors in Canada and Mexico. For this event and a rich set of firms listed in the United States with foreign affiliates in Mexico and/or Canada, we find statistically significant and robust negative abnormal returns consistent with a positive and economically relevant value of ISDS. The fourth chapter evaluates the impact of expropriation risk on trade in value added. In particular, this chapter argues that the host government’s appearance in an ISDS-proceeding conveys an important signal about the country’s compliance with property rights. The registration of an ISDS case reveals that the government was not willing to settle a dispute with an investor out of court and that this investor is determined to bear arbitration costs in order to challenge the host’s policy. Besides the filing of ISDS cases, also awards from arbitration panels are valuable news to the investment community. If the tribunal decides against the government, foreign investors are expected to adapt their assessment of expropriation risk in the host state. Multinationals understand that the existence of investment treaties could not deter the government from taking measures that illegally diminish the value of foreign investments. As a result, investment flows to the host country and therefore trade in value added with the host country should decline. Based on a sample that encompasses 5 sectors, 189 countries and 26 years, I indeed find that losing investor-state dispute settlement cases decreases value added exports to the host government’s economy. This trade reducing effect is substantial even in the short-term and is larger for non-OECD countries. I also provide evidence that even the initiation of these international arbitration proceedings harms the host’s reputation. Concerning the investor’s country of origin, particularly value added trade flows from the primary and low-tech services industry are affected by bilateral investment disputes. Eventually, my results indicate that effects are not restricted to the claimant’s sector but spill over to other industries that are not directly involved in the dispute.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".