Social Scientist PhD | Data Scientist | Mixed Methods Political Economy Specialist
diana.m.stanescu[at]gmail.com
I am a social scientist with 9+ years experience and expertise in economic and foreign policy analysis, as well as qualitative and quantitative methods. I obtained my PhD in 2020 from the Department of Politics at Princeton University. My work was supported by Stanford University’s Walter H. Shorenstein Asia-Pacific Research Center, Harvard University's Program on U.S.-Japan Relations, Princeton University's Center for International Security Studies, Institute for International and Regional Studies, East Asia Program, and the Lynde and Harry Bradley Foundation.
How can scholars conduct field research when there is limited access to the field? This article first identifies how limited and uncertain field access can affect field research and then provides recommendations to address these challenges. We focus on conducting field research in Japan because of our substantive expertise, but we believe that the problems and solutions outlined in this article are applicable to a broad range of countries. Our hope is that this article contributes to the developing literature on conducting research during times of emergency and to the larger literature on best practices for field research.
Recent research has highlighted the importance of bureaucracies in shaping trade policy. What are the mechanisms underlining this relationship? I argue that more autonomous and consolidated bureaucratic structures support trade liberalization via two mechanisms: by limiting interest groups' access to bureaucratic processes and networks, as well as by reducing the number of veto players. This paper features a within-case study of Japan to illustrate mechanisms for how interest groups maneuver within bureaucratic structures to exert influence over trade policy. It leverages the bureaucratic reforms Japan experienced since late 1990s to show reduced interest group access during periods of increased autonomy and consolidation drove trade liberalization. In contrast, increased access during periods of lower bureaucratic autonomy led to less trade liberalization.
How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.
This article documents an approach to predicting children’s well-being using data from the Fragile Families and Child Wellbeing Study, which are representative of births in large U.S. cities. The authors use the least absolute shrinkage and selection operator (LASSO) to preprocess the data. They then apply the Amelia algorithm to impute missing data. Finally, they use LASSO again for prediction with the imputed data. The authors report the performance of this approach for six outcome variables. The approach achieves the best performance for the variable material hardship. The out-of-sample mean squared error of the authors’ prediction is 0.019, the lowest among all submissions in the Fragile Families Challenge. The authors find that among variables with high predictive power, variables from mother surveys dominate. Furthermore, components of material hardship in the past strongly predict current material hardship.
How do individual firms manage risks and benefits associated with foreign direct investments (FDI)? This paper argues that bureaucratic ties with the home government, or the government of their country of origin, impact firms' FDI strategies. Specifically, we propose that firm-level ties with the home government, facilitated by revolving door hiring, encourage firms to invest abroad via two mechanisms: by bringing information and resources that the home government can offer, and by giving the firm a better sense of protection against future expropriation risks. To test this theory, we utilize micro-level data in Japan, where public reporting of re-employment of retired civil servants has been mandated since 2009. By combining this unique information with a firm-level business activity survey conducted by the Japanese government, covering the investment activities of 24,870 firms, we construct a full network of bureaucracy-firm connections and FDI activities between 2010-2017. Our empirical analysis reveals that firms with more bureaucratic ties at home are more likely to engage in FDI activities. Our findings suggest that the value of government connections extends to firms' business activities beyond the domestic market.
Foreign trade is at the nexus of commerce and diplomacy. How do states balance both interests? The majority of governments seek to maximize economic returns from trade through locating trade within a commerce ministry. But governments with a higher demand for linking trade and foreign policy unite both policies within the foreign ministry jurisdiction. Surprisingly few follow the United States model of a separate agency for trade. We argue that the structure of trade policy reveals underlying government priorities. Using an original dataset of comparative trade policies for all WTO members over the period 1995-2017 coded from WTO Trade Policy Reviews, we evaluate the conditions that influence the structure of trade policy. Case studies explore debates over changes to the design of the trade portfolio in Canada and South Korea. Then we evaluate how trade bureaucracy design choices influence the selection of partners and treaty design for preferential trade agreements. We find that foreign ministries stand out for their willingness to form PTAs that extend beyond alliance partners and add security provisions in the economic agreements.
Despite the bureaucracy's central role in shaping how competing preferences are aggregated into policy, studies of trade policy have largely neglected its role. This paper argues interest group input can empower bureaucrats with more information, but it also leads to narrowly targeted interests increasingly gaining control over policy. This effect is mitigated by bureaucratic structures endowed with more independence and internal expertise, and which are less reliant on formalized channels of industry participation. I take advantage of WTO reports to construct a dataset that identifies all bureaucracies in charge of trade policy and categorize their structure across a panel of 135 countries and 20 years. The empirical test assesses the effect of bureaucracies on non-tariff barriers - a form of administered protection. I find that bureaucracies with apolitical expertise implement policies that are less protectionist than those that engage active industry participation, controlling for macroeconomic shocks and confounders for institutional design.
Scholars of international cooperation argue that member states delegate decision making authority to international organizations (IOs) as a commitment to non-interference. We argue this logic conflates the objects of delegation with the mechanisms by which delegation is made credible. Member states delegate decision making authority to international bureaucrats. The credibility of delegation depends on institutional features of the relevant IO. Where delegation is credible, individual bureaucrats will exercise an independent impact on policy making. We test the credibility of delegation within the International Monetary Fund (IMF). We develop a formal model of bureaucratic appointments, characterize their equilibrium impact on market valuations of sovereign debt, and provide causal estimates of this impact employing event study methods. Our analytical results provide a direct test of the credibility of delegation as well as a transparent theoretical interpretation of the causal estimand. We find strong and consistent support for the credibility of delegation within the IMF.
Ph.D.-level intensive course. Instructor (with Erik Wang and Naoki Egami).
This course prepares graduate students for the Politics department’s quantitative methods sequence. It presents the basics of statistical programming using R, an open-source computing environment. Using data from published journal articles, students learn how to manipulate data, create graphs and tables, and conduct basic statistical analysis.
Assistant instructor to Prof. Keren Yarhi-Milo. Advanced undergraduate course. 2 weekly sessions of 5-10 students.
How do US presidents make foreign policy decisions? The class will review the constraints, dilemmas, risks and opportunities that American presidents face during international crises and wars. It will expose students to alternative explanations for how states make foreign policy, with an emphasis on the decision-making process. We will critically analyze the decision-making process that led to the undertaking of major and historical decisions in the US history and will conduct simulations of potential crisis scenarios.
Assistant instructor to Prof. Kosuke Imai (Politics) and Prof. Margaret Frye (Sociology). Introductory statistics and data analysis undergraduate course. 4 sessions per week of 10-15 students.
Would universal health insurance improve the health of the poor? Do patterns of arrests in US cities show evidence of racial profiling? What accounts for who votes and their choice of candidates? This course will teach students how to address these and other social science questions by analyzing quantitative data. The course introduces basic principles of statistical inference and programming skills for data analysis. The goal is to provide students with the foundation necessary to analyze data in their own research and to become critical consumers of statistical claims made in the news media, in policy reports, and in academic research.