Complex policy problems like climate change and illicit finance require a diverse methodological repertoire and an agnostic approach to selecting the appropriate analytical tool to accomplish discrete inferential tasks. Drawing from the disciplines of political science, economics, and statistical data science, this dissertation tackles three distinct problems on causal evaluation, measurement, and missing data. The first paper evaluates the causal effect of a climate mitigation policy on the carbon emissions of the UK. Using a synthetic control estimator, this chapter finds that post-treatment emissions in the UK were 10% lower than what they would have been without the climate policy. The results imply that voluntary climate reforms that make concessions to domestic producers are still able to meaningfully reduce emissions, even in the absence of a legally binding global climate treaty. The second paper presents a novel methodology to measure illicit trade flows and originates the "atlas of misinvoicing", the first database to provide comprehensive bilateral estimates of the dollar amount of misinvoiced trade disaggregated by commodity sector for 167 countries during 2000-2018. Results show that African countries lost on average $86 billion a year in gross illicit outflows during that period, and that the biggest source of illicit trade on the continent was the natural resources sector. The findings suggest that combating illicit financial flows will be crucial to providing finance for sustainable development and to promoting domestic resource mobilization in poor countries. The third paper proposes a machine learning approach to ameliorate the problem of missing data from developing countries, where administrative systems for data collection tend to be weaker. Some African countries do not provide customs declarations, which the "atlas" method requires as input data. This chapter predicts illicit trade using machine learning models that are trained on readily available data without relying on official trade statistics. Findings show that the models are able to recover 70% of the variation in illicit trade outcomes. This demonstrates the promise of predictive approaches to augment existing measures of illicit finance in data-constrained settings. Broadly, the chapters in this dissertation can be understood as operating in the different scientific frameworks of causal, descriptive, and predictive inference, respectively. Tackling difficult environmental and developmental problems will require a willingness to traverse methodological siloes in order to identify the best tool for the job – this dissertation contributes to pushing the search for solutions forward.

Environmental and social issues involving firms often arise due to difficulties in observing their environmental and social performance. Firms’ greenhouse gas emissions, toxic releases, accounting scandals, insider trading, and child labor abuse are all such cases where stakeholders face challenges in detecting and addressing them beforehand. Therefore, it is often helpful for stakeholders of firms (such as customers, government, investors, etc.) to have reliable and observable information available in normal times to accurately assess firms’ unobservable qualities.

When reliable and direct information about a firm’s unobservable qualities is unavailable, stakeholders might turn to a collective reputation of firms to evaluate difficult-to-observe qualities. A collective reputation refers to stakeholders’ beliefs about which firms belong to a specific group and the stereotype of the qualities and characteristics common to that group. By utilizing a collective reputation, stakeholders associate a firm with a broader group through a common observable trait, and then use their stereotype about that group to infer the firm's other, more difficult-to-observe qualities.

In my dissertation, I propose that a collective reputation is a combination of three attributes: group membership, group stereotype, and salience. Each of these attributes is the subject of my three dissertation studies, where I investigate how changes in each of them affect stakeholders’ evaluation of firms. The first study examines how changes in a firm’s group membership affect its financial performance, using the case of South Korea’s business group firms, known as Chaebol. The second study investigates how changes in stakeholders’ stereotypes about the group influence their investment in a new venture start-up within the context of entrepreneurship. The third study examines how changes in the salience of a collective reputation due to information disclosure affect the financial performance of firms, utilizing the case of the US EPA’s TRI (Toxic Release Inventory) program.

Changes in a collective reputation can significantly impact firms’ financial performance, and thus it is crucial for business practitioners to clearly understand the mechanism of how a collective reputation works and how stakeholders utilize it to evaluate firms’ unobservable qualities. Throughout my dissertation and each chapter, I provide business and policy implications on how practitioners can better use a collective reputation to enhance business sustainability and financial performance.

More than ever, corporations face pressure to act beyond their fiduciary duties to shareholders and regulatory requirements to reduce their environmental impact and improve social conditions, yet frequently produce empty symbolic measures with no benefit to societal welfare or their own financial performance. This research program examines both external incentives for firms to engage in strategic provision of social and environmental goods and information strategies to harness sustainability motivations and influence perceptions among employees and other stakeholder groups. The dissertation consists of four chapters, each comprising a standalone empirical research study grounded in strategic management, economics, and behavioral theories. The first two studies use field experimental methods to examine the tendency for individuals to alter attitudes and behavior in response to information about relevant peers; the first study in a residential community and the second in a corporate workplace. The third study extends these behavioral phenomena to corporations, evaluating the degree to which more profitable or more rivalrous industry peers influence firms’ engagement in corporate social responsibility initiatives. The final study examines microdata contained within a prominent third-party corporate greenhouse gas emissions disclosure program, finding evidence of widespread reporting inconsistencies that suggest systematic efforts by companies to mislead stakeholders about actual carbon management performance. The outcomes of this research program inform corporate strategies for leveraging social and environmental goods for improved financial performance --- the triple bottom line --- and policy prescriptions to enhance incentives for companies to provide truthful disclosures of environmental performance.

In resourced-constrained countries like India, ambitions for environmental protection are often limited by the paucity of funds, and limited capacity within governments to implement transformational programs. But an excessive focus on funding and government action fails to account for several ways in which motivated individuals and communities voluntarily come together to solve environmental problems. Such initiatives might be small and dispersed but can be scaled-up by understanding the underlying structure of incentives and motivations that drive people towards contributing labour and finding collective solutions. My dissertation is motivated by the desire to develop practical insights for fostering greater citizen participation and collective action. In particular, my research is focused on understanding how low-cost and non-monetary incentives motivate individuals towards pro-social and pro-environmental behaviours.

The first project examines the factors that contribute to better performance on tasks that managers cannot easily observe. Here, I study frontline employees of an NGO in India who are responsible for improving social development outcomes for rural women. These employees perform two broad categories of tasks – some are observable by their managers and others are more difficult to observe or unobservable. Unobservable tasks like cajoling, convincing, dispute resolution, and emotional labour are critical for frontline work and meeting the NGO’s organizational mission. However they remain unrewarded because they are not observed. Why do frontline employees perform these tasks then? Through a survey of 15,000 rural women and 150 frontline employees, I find that pro-social motivation is associated with improved performance on all types of tasks. On the other hand, I find that monitoring is not associated with improved performance. I also find that understanding the broad principles for action are more important than knowing which specific tasks the management wants employees to execute. The results suggest that managers can improve performance at the frontlines by selecting motivated workers, and by allowing them autonomy to carry out their tasks by reducing the extent of monitoring and supervision.

The second project explores incentives for performance improvement in a national ranking program for cities in India. The Swachh Survekshan is an initiative by the Indian national government for ranking cities on their performance on waste management and sanitation outcomes. Since 2016, the program has scored and ranked cities to motivate performance by inducing the spirit of competition. However, the national government has also frequently changed the metrics by which cities are scored. Utilising this natural experiment, I ask two questions: a) what motivates national governments to engage in target-shifting?, and b) how to cities respond to target-shifting? I develop an original dataset of performance scores and ranks for over 400 cities, supplemented by data on revenue generated by 243 cities and qualitative insights from interviews with government officials and consultants. I find that target-shifting occurs to inflate scores and enhance the reputation of the program, as compared to an alternative scenario in which target-shifting occurs as a result of policy-learning. I also find that cities distort their data in response to target-shifting. However, these distortions are caused less by a conscious effort to “game” the rankings but result from the lack of data management capacity. The results suggest that ranking programs in the public sector are highly prone to distortions by both national and sub-national governments. Instead of selecting winner and losers, alternative strategies for performance improvement that focus on self-assessment and capacity building might be more feasible for the public sector.

The third project examines how just and democratic India’s solar energy policies are. Most commonly, decisions and policies for solar energy development are justified on the basis on mitigating climate change or cost-benefit analyses. Elements such as justice and democracy are relatively new considerations in the policy discourse. I presents a framework for analysis of these concepts grounded in the context of the Global South. With respect to this, I define the articulation of distributional and procedural goals in policy as two pillars of a just and democratic energy transition. Through an analysis of over 30 renewable energy policies, I find that in terms of distributional goals, most policies continue to exclude significant marginalized groups. Where groups are included, the focus is more on identifying them rather than recognizing their specific needs or the processes by which they can effectively transition to becoming full consumers of electricity. Further, distributional goals seeking to create equity beyond access are not substantiated by an allocation of policy-tools to foster the cross-sectoral collaboration required for their implementation. With respect to procedural goals, instruments that facilitate ownership and ease transactions were emphasized and elaborated on more than those that decentre legacy institutions or enhance just participation. Overall, the policies tend to keep the system in its current configuration and forego the opportunity solar provides to create transformative change beyond reducing emissions.