Suzanne McCoskey

A residual-based test of the null of cointegration in panel data

This paper proposes a residual-based Lagrange Multiplier (LM) test for the null of cointegration in panel data. The test is analogous to the locally best unbiased invariant (LBUI) for a moving average (MA) unit root. The asymptotic distribution of the test is derived under the null. Monte Carlo simulations are performed to study the size and power properties of the proposed test. Overall, the empirical sizes of the LM- FM and LM-DOLS are close to the true size even in small samples. The power is quite good for the panels where T >50, and decent with panels for fewer observations in T. In our fixed sample of N=50 and T=50, the presence of a moving average and correlation between the regressor errors and regressors causes the two tests to perform quite differently, complicating the choice of estimation procedures. In general, the LM- DOLS test seems to be better at correcting these effects, although in some cases the LM-FM test is more powerful. Although much of the non- stationary time series econometrics has been criticized for having more to do with the specific properties of the data set rather than underlying economic models, the recent development of the cointegration literature has allowed for a concrete bridge between economic long run theory and time series methods. Our test now allows for the testing of the null of cointegration in a panel setting and should be of considerable interest to economists in a wide variety of fields.

Health care expenditures and GDP: panel data unit root test results

This short paper presents unit root test results for time series on per capita national health care expenditures and gross domestic product in the OECD. Unlike the country-by-country test used by [Hansen, P., King, A., 1996. The determinants of health care expenditure: A cointegration approach. J. Health Econ, 15, 127-137], the test we employ exploits the panel nature of the OECD data. Using this approach, we are able to reject the null hypothesis that these series contain unit roots. No single test is likely to be definitive in this rapidly-evolving area of econometric research; however, our results help to mitigate concern that panel data analyses of national health care expenditures are misspecified.

Estimation and inference of a cointegrated regression in panel data: a Monte Carlo study

SYNOPTIC ABSTRACTThis paper studies the finite sample properties of the least squares dummy variable (LSDV) estimator and t-statistic in a cointegrated regression in panel data. Through Monte Carlo studies we find that both the LSDV estimator and the t-statistic have a small amount of bias, and the t-statistic diverges as the cross-sectional dimension increases. We also find that the bias-corrected LSDV estimator and the bias-corrected t-statistic do not reduce the magnitude of the bias problem.

A Monte Carlo Comparison of Tests for Cointegration in Panel Data

This paper surveys recent developments and provides Monte Carlo comparison on various tests proposed forcointegration in panel data. In particular, tests for two panel models, varying intercepts and varying slopes, and varying intercepts and common slopes are presented from the literature with a total of seven tests being simulated. In all cases, results on empirical size and size-adjusted power are given.

Does Global Meat Consumption Follow an Environmental Kuznets Curve

Abstract In this article, we use data on meat consumption, per capita income, and other socioeconomic variables for 150 countries to determine whether data support the hypothesis that per capita meat consumption follows a Kuznets-style inverted U-curve. In other words, as nations increase their real per capita incomes, while individuals at first consume more meat, ultimately, over time and with increased income, do they moderate their consumption? Our results signal that although there is evidence of a Kuznets relationship, the income at which our data suggests a deceleration of meat is large enough that for many countries this deceleration will not be reached in the foreseeable future. In a cross-section sample of low-income countries, we find no evidence of a Kuznets relationship. In a cross-section sample of high-income countries, we do find a potential Kuznets relationship and a deceleration of meat consumption at a per capita income of US

Testing the Stability of a Production Function with Urbanization as a Shift Factor: An Application of Non-Stationary Panel Data Techniques

49,848. In the full panel-data sample combining high- and low-income countries, including data on land area and urbanization, our results suggest an inflection point in meat consumption at an income of US

Near integration, bank reluctance, and discount window borrowing

36,375, still quite high for any realistic impact. Thus, our results highlight that effectively decelerating the global demand for meat may require aggressive and potentially controversial policy interventions, which, while leaving individuals with less choice, would address the otherwise devastating environmental impacts of increasing meat consumption.

Testing the Stability of a Production Function with Urbanization as a Shift Factor

Urban economists have long sought to explain the relationship between urbanization levels and output. In this paper we revisit this question and test the long-run stability of a production function with urbanization using non-stationary panel data techniques. Our results show that a long-run relationship between urbanization output per worker and capital per worker cannot be rejected for either our sample of 30 developing countries or our sample of 22 developed countries. In addition, we estimate the long-run average effects on GDPW of urbanization and capital. These results offer newer insights and potential for dynamic urban models than the simple cross-section approach.

A Panel Data Investigation of the Relationship Between Urbanization and Growth

Abstract This study puts forth stationarity considerations in explaining the observed breakdown between aggregate Discount Window borrowing and the spread between the Federal Funds rate and the discount rate during the post-1987 period. Tests with biweekly data indicate stationarity for adjustment borrowing, but cannot reject the unit root for the spread. The Goodfriend–Dutkowsky dynamic implicit cost formulation can accommodate the contrasting stationarity properties. Structural restrictions are compatible with stationary borrowing and a stationary or near integrated spread. While empirical findings from the static model indicate greater bank reluctance to borrow over time, the dynamic model gives considerably less support.