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Category Archives: Charles Becker

Neighborhood Effects and School Performance: The Impact of Public Housing Demolitions on Children in North Carolina

By Rebecca Aqostino

This study explores how the demolitions of particularly distressed public housing units, through the Home Ownership for People Everywhere (HOPE VI) grants program, have affected academic outcomes for children in adjacent neighborhoods in Durham and Wilmington, North Carolina. I measure neighborhood-level changes and individual effects through regression analysis. All students in demolition communities are compared to those in control communities: census blocks in the same cities with public housing units that were not demolished. Those in the Durham experiment community experienced statistically significant gains when compared to those in the control communities; the effect is insignificant in Wilmington.

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Advisor: Charles Becker | JEL Codes: C23, H41, H52, H75, I24, I25 | Tagged: Achievement, Demolitions, Distressed Housing, HOPE VI, Neighborhood Effects, Public Housing, School Performance

The Comprehensive Optimal Business Location Model

By Mitchel Gorecki

In order to ensure long run viability, a firm must understand the idea of optimal business location. In the designing of a strategy, it is important to not only evaluate the present market environment but to also account for possible future change. This paper will demonstrate the core ideas behind a comprehensive location model that will predict the optimal location for a business. The effectiveness of the model will be evaluated by using past data from Durham, North Carolina to predict current retail development. The model is determined to be successful by seeing if the trend recognized would be able to correctly identify the present location choices of firms. The model will be further used to predict the future development plans for businesses locating in the Durham area.

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Advisor: Charles Becker

Measuring the Likelihood of Small Business Loan Default: Community Development Financial Institutions (CDFIs) and the use of Credit-Scoring to Minimize Default Risk1

By Andrea Coravos

Community development financial institutions (CDFIs) provide financial services to underserved markets and populations. Using small business loan portfolio data from a national CDFI, this paper identifies the specific borrower, lender, and loan characteristics and changes in economic conditions that increase the likelihood of default. These results lay the foundation for an in-house credit-scoring model, which could decrease the CDFI’s underwriting costs while maintaining their social mission. Credit-scoring models help CDFIs quantify their risk, which often allows them to extend more credit in the small business community.*

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Advisor: Charles Becker

Currency Crisis Early Warning Systems: Robust Adjustments to the Signal-Based Approach

By Andrew Kindman

This research proposes and tests several novel strategies for enhancing the strength of conventional, signal-based currency crisis Early Warning Systems (EWS). Using country level, monthly macroeconomic time-series data, it develops an algorithmic process for identifying periods of elevated currency crisis risk and achieves robust results. The proposed changes to current EWS include: 1) an adjustment to the process by which crises are identified empirically, 2) the addition of control panels to dampen the prevalence of false positives, 3) the addition of inter-temporal interaction terms that strive to bring the forecasting model in line with contemporary theoretical models of currency crisis, and 4) the addition of an algorithm for controlling post-crisis bias in macroeconomic trends. In out-of-sample, post-estimation analysis, the system is able to identify 75% of crisis incidents while generating false positives at a rate of less than 20%. Currency crisis EWS have challenged economists for some time, and though these results are not directly comparable to current EWS based on differences in reporting strategies, they are strong enough to warrant further investigation, particularly for applicability as policy instruments.

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Advisor: Charles Becker, Kent Kimbrough

Cell Phones and Cattle: The Impact of Mobile Telephony on Agricultural Productivity in Developing Nations

By Daniel Houghton

This paper examines the impact of mobile telephony on productivity in developing nations. Previous studies have suggested that mobile phones have real impacts on economic outcomes in these countries. Using micro-data from Swaziland, Cambodia, and Honduras, this study looks to identify the effects of mobile phone ownership on household productive outcomes in a two-stage regression. The results provide significant evidence that mobile phone ownership does indeed improve productivity at the household level.

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Advisor: Charles Becker

To Work or Not to Work? Labor Supply Decisions of Russia’s Disabled

By Aleksander Andreev

By some estimates, almost 6% of Russians are officially disabled. The Russian government has announced the rehabilitation of disabled individuals into the labor force as one of its goals. This paper investigates labor supply decisions of Russia’s disabled using data from the cross-sectional NOBUS dataset. Particular emphasis will be made on differences in disability and employment trends across various strata of the Russian population. The paper concludes that Federal disability pension policy does not substantially disincentivize employment. A key finding is that employment decisions are based primarily on health status, family dynamics, and local opportunities.

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Advisor: Charles Becker

Questions?

Undergraduate Program Assistant
Jennifer Becker
dus_asst@econ.duke.edu

Director of the Honors Program
Michelle P. Connolly
michelle.connolly@duke.edu