Basu, Deepankar

Job Title

Professor, Department of Economics, University of Massachusetts Amherst

Last Name

Basu

First Name

Deepankar

Discipline

Economics

Expertise

Applied econometrics
Development economics
Political economy

Introduction

Deepankar Basu specializes in applied econometrics with a focus on Marxian political economy, and economic development.

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Now showing 1 - 10 of 58

Global Value Chains and Unequal Exchange: Market Power and Monopoly Power
(2021) Basu, Deepankar; Vasudevan, Ramaa
We revisit the hypotheses of unequal exchange and deteriorating terms of trade in the specific context of import-intensive, export- led strategies of developing countries which rely on integration into GVCs for access to markets in developed countries using a stylized two-country two-commodity Classical- Marxian trade model. Two sources of asymmetry can be distinguished: market power arising from the competition between suppliers that depresses the prices at which the final good is supplied; and monopoly power arising from the lead firms control and ownership of intangible assets including brand and design. The model explores some implications of these two sources of asymmetry.
Bounding Sets for Treatment Effects with Proportional Selection
(2021) Basu, Deepankar
In linear econometric models with proportional selection on unobservables, omitted variable bias in estimated treatment effects are roots of a cubic equation involving estimated parameters from a short and intermediate regression, the former excluding and the latter including all observable controls. The roots of the cubic are functions of δ, the degree of proportional selection on unobservables, and Rmax, the R-squared in a hypothetical long regression that includes the unobservable confounder and all observable controls. In this paper a simple method is proposed to compute roots of the cubic over meaningful regions of the δ-Rmax plane and use the roots to construct bounding sets for the true treatment effect. The proposed method is illustrated with both a simulated and an observational data set.
Farmer Suicides in India: Levels and Trends across Major States, 1995-2011
(2016) Basu, Deepankar; Das, Debarshi; Misra, Kartik
In the paper, we use data on farmer suicides from the National Crime Records Bureau and population data from the Censuses of 1991, 2001 and 2011 to estimate the suicide mortality rate (SMR) of farmers and non-farmers for 19 major states of India and for the country as a whole. We use movements in the SMR ratio ratio of farmer SMR and non-farmer SMR) to understand the level and trend of the problem of farmer suicides across states and over time. For the country as a whole, and for many individual states, the SMR ratio has increased over time. This suggests that the problem of farmer suicides has become more severe across large swathes of the country, and calls for immediate and well planned policy interventions.
Covariate Benchmarking for Sensitivity Analysis when the Confounder is Correlated with Observed Covariates
(2023) Basu, Deepankar
Covariate benchmarking is an important part of sensitivity analysis about omitted variable bias and can be used to bound the strength of the unobserved confounder using information and judgments about observed covariates. It is common to carry out formal covariate benchmarking under the assumption that the unobserved confounder is orthogonal to the observed covariates. This assumption is restrictive and will be difficult to defended in most empirical analyses. In this paper I show that relaxing the orthogo- nality assumption leads to a breakdown of a recently proposed innovative formal covariate benchmarking methodology.
Public Debt and Growth: An Assessment of Key Findings on Causality and Thresholds
(2017) Ash, Michael; Basu, Deepankar; Dube, Arindrajit
We provide a comprehensive assessment of the relationship between public debt and GDP growth in the postwar advanced economies. We use the timing of changes in public debt and growth to account for endogeneity, and find little evidence of a negative relationship. Semi-parametric estimates do not indicate any threshold effects. Finally, we reconcile our results with four recent, influential papers that found a substantial negative relationship, especially when public debt exceeds 90 percent of GDP. These earlier results appear to derive mostly from peculiar parametric specifications of nonlinearities, or use of small samples which amplify the influence of outliers.
Replacement versus Historical Cost Profit Rates: What is the difference? When does it matter?
(2012-12) Basu, Deepankar
This paper explains the BEA methodology for computing historical cost and replacement cost measures of the net stock of capital in the U.S. economy. It is demonstrated that there exists a threshold rate of inflation in the price of capital goods that keeps the percentage difference between the two capital stock measures constant. Hence, over periods when average inflation in the price index for capital goods is equal to the threshold value, historical cost and replacement cost profit rates would show equal percentage changes; an example of such a period for the U.S. economy is the whole postwar period 1946–2010. Moreover, trends in both replacement cost and historical cost profit rates display very similar movements over long periods, making the choice of capital stock valuation irrelevant for empirical analysis of profitability trends.
Bias of OLS Estimators due to Exclusion of Relevant Variables and Inclusion of Irrelevant Variables
(2018) Basu, Deepankar
In this paper I discuss three issues related to bias of OLS estimators in a general multivariate setting. First, I discuss the bias that arises from omitting relevant variables. I offer a geometric interpretation of such bias and derive sufficient conditions in terms of sign restrictions that allows us to determine the direction of bias. Second, I show that inclusion of some omitted variables will not necessarily reduce the magnitude of OVB as long as some others remain omitted. Third, I show that inclusion of irrelevant variables in a model with omitted variables can also have an impact on the bias of OLS estimators. I use the running example of a simple wage regression to illustrate my arguments.
Formal Covariate Benchmarking to Bound Omitted Variable Bias
(2023) Basu, Deepankar
Covariate benchmarking is an important part of sensitivity analysis about omitted variable bias and can be used to bound the strength of the unobserved confounder using information and judgments about observed covariates. It is common to carry out formal covariate benchmarking after residualizing the unobserved confounder on the set of observed covariates. In this paper, I explain the rationale and details of this procedure. I clarify some important details of the process of formal covariate benchmarking and highlight some of the difficulties of interpretation that researchers face in reasoning about the residualized part of unobserved confounders. I explain all the points with several empirical examples.
Does the Steindl-Dutt Investment Function Rule Out Profit-Led Expansion?
(2018) Basu, Deepankar
Bhaduri and Marglin (1990) had argued that an investment function which has the profit rate and the capacity utilization rates as the two determinants of investment imposes unwarranted restrictions on the macroeconomic model and rules out profit-led expansion. In this paper, I show that this critique only holds in a closed economy model. In an open economy model, such an investment function does not rule out profit-led expansion. I argue that the problem was less in the investment function itself than in the larger model within which it was embedded, in particular the saving behavior of the macroeconomy entailed by the model.
Alternative Approaches to Labor Values and Prices of Production: Theory and Evidence
(2023) Basu, Deepankar; Moraitis, Athanasios
In this paper, we discuss three approaches to estimating classical prices of production(long run equilibrium prices) in both a circulating capital model and a model that includes capital stock: the Standard Interpretation of Marx’s value theory, the New Interpretation of Marx’s value theory, and the Sraffian approach to prices of production. We add two refinements to both models: (a) allowing for differential wages rates across industries; and(b) taking account of unproductive industries in labor value calculations. We implement(a) the circulating capital models using harmonized input-output data from the World Input Output Database for 37 countries for the period 2000–2014, and (b) the model with capital stock for the U.S. economy using input-output and other relevant data for 2020.For all models, we estimate labor values, prices of production and the uniform rate of profit. We test for deviation between relative labor values and relative prices of production using both regression and non-regression-based methods. For both the circulating capital model and the model with capital stock, we find that the vector of relative labor values and the vector of relative prices of production are far apart in terms of both regression and non-regression-based measures.