Long-Run Effects of Incentivizing Work After Childbirth

May 2020

Elira Kuka (George Washington University, IZA, and NBER) and Na’ama Shenhav (Dartmouth College and NBER)

IIEP working paper 2020-10

Abstract: This paper uses a panel of SSA earnings linked to the CPS to estimate the impact of increasing post-childbirth work incentives on mothers’ long-run career trajectories. We implement a novel research design that exploits variation in the timing of the 1993 reform of the Earned Income Tax Credit (EITC) around a woman’s first birth and in eligibility for the credit. We find that single mothers exposed to the expansion immediately after a first birth (“early-exposed”) have 3 to 4 p.p. higher employment in the 5 years after a first birth than single mothers exposed 3 to 6 years after a first birth (“late-exposed”). Ten to nineteen years after a first birth, early-exposed mothers have the same employment and hours as late-exposed mothers, but have accrued 0.5 to 0.6 more years of work experience and have 6 percent higher earnings. Incorporating long-run effects on EITC benefits and earnings increases the implied marginal value of public funds (MVPF) of the expansion. Our results suggest that there are steep returns to work incentives at childbirth that accumulate over the life-cycle.


JEL Codes: J16, J31, H2

Key Words: child penalty, EITC

Medieval Cities Through the Lens of Urban Economic Theories

May 2020

Remi Jedwab (George Washington University), Noel D. Johnson (George Mason University), and Mark Koyama (George Mason University)

IIEP working paper 2020-9

Abstract: We draw on theories and empirical findings from urban economics to explore and explain patterns of city growth in the Middle Ages (c. 800-1500 CE). We discuss how agricultural development and physical geography determined the location and size of cities during the medieval period. We also consider the relative importance of economies of scale, agglomeration, and human capital spillovers in medieval cities and discuss how their growth was limited by disamenities and constraints on mobility. We discuss how medieval cities responded to shocks such as the Black Death and describe how institutions became increasingly important in determining their trajectories. Avenues for future research are also laid out.


JEL Codes: R11; R12; R19; N9; N93; N95

Key Words: Medieval Era; City Growth; Urbanization; Food Surplus Hypothesis; Agglomeration Effects; Labor Mobility; Pandemics; Institutions; Europe; Asia

A Plurilateral “Single Data Area” Is the Solution to Canada’s Data Trilemma

September 2019

Susan A. Aaronson and Patrick Leblond

IIEP working paper 2020-8

Summary: With its relatively small population, Canada faces a challenge in terms of the amount of high-quality data that it can generate to support a successful data-driven economy. As a result, Canada needs to allow data to flow freely across its borders. However, it also has to provide a high-trust data environment if it wants individuals, firms and government to participate actively in such an economy. As such, Canada (and other countries) faces what can be called the data trilemma, whereby it is not possible to have simultaneously data that flows freely across borders, a high-trust data environment and a national data protection regime; one of these three objectives has to give so that only two are effectively possible at the same time.

To resolve the data trilemma, Canada should work with its key economic partners — namely the European Union, Japan and the United States — to develop a single data area that would be managed by an international data standards board. The envisioned single data area would allow for all types of personal and non-personal data to flow freely across borders while ensuring that individuals, consumers, workers, firms and governments are protected from potential harm arising from activities such as the collection, processing, use, storage or purchase/sale of data. If Canada and its economic partners share similar norms and standards for regulating data, then allowing data to flow freely across borders with these countries no longer risks undermining trust, which is crucial to a successful data-driven economy.

America’s uneven approach to AI and its consequences

April 2020

Susan A. Aaronson

IIEP working paper 2020-7

Introduction Excerpt: The world’s oceans are in trouble. Global warming is causing sea levels to rise and reducing the supply of food in the oceans. The ecological balance of the ocean has been disturbed by invasive species and cholera. Many pesticides and nutrients used in agriculture end up in the coastal waters, resulting in oxygen depletion that kills marine plants and shellfish. Meanwhile the supply of fish is declining due to overfishing. Yet to flourish, humankind requires healthy oceans; the oceans generate half of the oxygen we breathe, and, at any given moment, they contain more than 97% of the world’s water. Oceans provide at least a sixth of the animal protein people eat. Living oceans absorb carbon dioxide from the atmosphere and reduce climate change impacts. Many civil society groups (NGOs) are trying to protect this shared resource. As example, OceanMind uses satellite data and artificial intelligence (AI) to analyze the movements of vessels and compare their activities to historical patterns. The NGO can thus identify damaging behavior such as overfishing

Data Governance, AI, and Trade: Asia as a Case Study

April 2020

IIEP working paper 2020-6

Introduction Excerpt: The arc of history seems to be bending again towards the dynamic nations of Asia (Gordon: 2008). The countries and territories of the Asia Pacific region are both a locus for trade and a source of technology fueled growth. In 2017, Asia recorded the highest growth in merchandise trade volume in 2017 for both exports and imports (WTO: 2018, 32). UNCTAD reports that exports of digitally deliverable services increased substantially across all regions during the period 2005– 2018, with a compound annual growth rate ranging between 6 and 12 per cent (table III.1). Growth was the highest in developing countries, especially in Asia (UNCTAD: 2019, 66).

Artificial intelligence (AI) is already a leading source of growth for many Asian countries. The AI market in the Asia Pacific was estimated at around US $450 million in 2017 and is expected to grow at a compounded annual growth rate of 46.9% by 2022 (Ghasemi: 2018). Several analysts believe Asia’s AI growth will soon overtake the US (Lee: 2018; Ghasemi: 2018)

Data Is Dangerous: Comparing the Risks That the United States, Canada and Germany See in Data Troves

April 2020

Susan A. Aaronson

IIEP working paper 2020-5

Summary: Citizens of the United States, Canada and Germany know that the online world is simultaneously a wondrous and dangerous place. They have seen details about their activities, education, financial status and beliefs stolen, misused and manipulated. This paper attempts to examine why stores of personal data (data troves) held by private firms became a national security problem in the United States and compares the US response to that of Canada and Germany. Citizens in all three countries rely on many of the same data-driven services and give personal information to many of the same companies. German and Canadian policy makers and scholars have also warned of potential national security spillovers of large data troves. However, the three nations have defined and addressed the problem differently. US policy makers see a problem in the ownership and use of personal data (what and how) instead of in America’s own failure to adequately govern personal data. The United States has not adopted a strong national law for protecting personal data, although national security officials have repeatedly warned of the importance of doing so. Instead, the United States has banned certain apps and adopted investment reviews of foreign firms that want to acquire firms with large troves of personal data. Meanwhile, Canada and Germany see a different national security risk. They find the problem is where and how data is stored and processed. Canadian and German officials are determined to ensure that Canadian and German laws apply to Canadian and German personal and/or government data when it is stored on the cloud (often on US cloud service providers). The case studies illuminate a governance gap: personal data troves held by governments and firms can present a multitude of security risks. However, policy makers have put forward nationalistic solutions that do not reflect the global nature of the risk.

The Value of Reputation in Trade: Evidence from Alibaba

March 2020

Maggie X. Chen and Min Wu

IIEP working paper 2020-4

Abstract: We examine the role of an online reputation mechanism in international trade by exploring T-shirt exports on Alibaba. Exploiting rich transaction data and features of search and rating algorithms, we show that exporters displaying a superior reputation perform significantly better than peers with nearly identical true ratings and observables and the value of reputation rises with the level of information friction and the specificity of information. We develop a dynamic reputation model with heterogeneous cross-country information friction to quantify the effect of the reputation mechanism and find a 20-percent increase in aggregate exports fueled by a market reallocation towards superstars.

JEL Codes: F1, D8

Key Words: reputation, information, superstar, and Alibaba

Human Capital Accumulation at Work: Estimates for the World and Implications for Development

February 2020

Remi Jedwab, Asif Islam, Paul Romer, and Robert Samaniego

IIEP working paper 2020-3

Abstract: In this paper, we: (i) study wage-experience profiles and obtain measures of returns to potential work experience using data from about 24 million individuals in 1,084 household surveys and census samples across 145 countries; (ii) show that returns to work experience are strongly correlated with economic development – workers in developed countries appear to accumulate twice more human capital at work than workers in developing countries; and (iii) use a simple accounting framework to find that the contribution of work experience to human capital accumulation and economic development might be as important as the contribution of education itself.

JEL: O11; O12; O15; O47; E24; J11; J31

Keywords: Returns to Work Experience; Returns to Education; Human Capital Accumulation; Economic Development; Labor Markets; Development Accounting

The Financial Center Leverage Cycle: Does it Spread Around the World?

February 2020

Graciela Laura Kaminsky, Leandro Medina, Shiyi Wang

IIEP working paper 2020-2

Abstract: With a novel database, we examine the evolution of capital flows to the periphery since the collapse of the Bretton Woods System in the early 1970s. We decompose capital flows into global, regional, and idiosyncratic factors. In contrast to previous findings, which mostly use data from the 2000s, we find that booms and busts in capital flows are mainly explained by regional factors and not the global factor. We then ask, what drives these regional factors. Is it the leverage cycle in the financial center? What triggers the leverage cycle in the financial center? Is it a change in global investors’ risk appetite? Or, is it a change in the demand for capital in the periphery? We link leverage in the financial center to regional capital flows and the cost of borrowing in international capital markets to answer these questions. Our estimations indicate that regional capital flows are driven by supply shocks. Interestingly, we find that the leverage in the financial center has a time-varying behavior, with a movement away from lending to the emerging periphery in the 1970s to the 1990s towards lending to the advanced periphery in the 2000s.

Keywords: International Borrowing Cycles. Global and Regional Factors. Push and Pull Factors of Capital Flows. Financial Center Leverage Cycles.

JEL Codes: F30, F34, F65




Mismatch in Online Job Search

February 2020

Tara M. Sinclair and Martha E. Gimbel

IIEP working paper 2020-1

Abstract: Labor market mismatch is an important measure of the health of the economy but is notoriously hard to measure since it requires information on both employer needs and job seeker characteristics. In this paper we use data from a large online job search website which has detailed information on both sides of the labor market. Mismatch is measured as the dissimilarity between the distribution of job seekers across a set of predefined categories and the distribution of job vacancies across the same categories. We produce time series measures of mismatch for the US and a set of English-speaking countries from January of 2014 through December of 2019. We find that title-level mismatch is substantial, with about 33% of the labor force needing to change job titles for the US to have zero mismatch in 2019, but that it declined from 40% in 2014 as the labor market has tightened. Furthermore, over the same time period, the mix of job opportunities has shifted substantially, but in a way that has made the overall distribution of jobs more similar to the distribution of job seekers. We interpret this finding as evidence that mismatch between job seekers and employers eased due to jobs coming back in the slow recovery after the Great Recession.

JEL Codes: E24, J11, J21, J24, J40, J62

Keywords: Job search, vacancies, employment, unemployment

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