ECONOMICS 797W APPLIED TIME SERIES ECONOMETRICS SPRING 2017, UMASS AMHERST. Instructor: Deepankar Basu Phone:

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1 ECONOMICS 797W APPLIED TIME SERIES ECONOMETRICS SPRING 2017, UMASS AMHERST Instructor: Deepankar Basu Phone: Office: 310 Crotty Hall Classes: Monday, Wednesday 11:15-12:30pm in 309 Crotty Hall Office Hours: Tuesday 2:00-4:00pm, or by appointment About the course: This course will introduce students to the basic techniques of time series econometric analysis and encourage them to apply some of these techniques to investigate interesting and important issues in heterodox macroeconomics, radical political economy and the political economy of development. The material that will be discussed in the course can be divided into two broad topics: (a) analysis of stationary time series processes (both univariate and vector processes), and (b) analysis of non-stationary time series processes (both univariate and vector processes). Textbooks: The following textbooks will be used: Enders, Walter Applied Econometric Time Series. Third Edition. Hoboken, NJ: John Wiley & Sons. (This is available as an E-book through the UMass library website). Kleiber, C., and Zeileis, A Applied Econometrics with R (use R!). Springer. (This is available as an E-book through the UMass library website). Supplementary Textbooks and Material: The following textbooks can be used for reference: Hayashi, F Econometrics. Princeton, NJ: Princeton University Press. Hamilton, J. D Time Series Analysis. Princeton, NJ: Princeton University Press. Juselius, K The Cointegrated VAR Model: Methodology and Applications. Oxford: Oxford University Press. Lütkepohl, H Springer. New Introduction to Multiple Time Series Analysis, Berlin: 1

2 Shumway, R. H., and Stoffer, D. S Time Series Analysis and Its Applications: With R Examples. Second Editon. Springer Texts in Statistics. New York: Springer. (This is available as an E-book through the UMass library website). Statistical Packages: We will primarily work in the open source software environment for statistical computing and graphics called R. The following resources can be used to learn working in R. Kleiber, C., and Zeileis, A Applied Econometrics with R (use R!). Springer. (This is an excellent resource and is available as an E-book through the UMass library website). Farnsworth, G Econometrics in R R time series quick fix. Quick-R. Grading: A total of 100 points will be divided between 5 take-home assignments and a replication or research paper as follows: Take-home assignments: The 5 take-home assignments will be worth a total of 50 points, with each contributing 10 points. The assignments will be handed out in class and will be due in about 7-10 days; they will involve solving end-of-chapter problems, and data exercises. Data exercises can be completed using R or STATA. Details of tutorial sessions to help familiarize students with R will be announced in class. Replication or Research paper: The paper will be worth 50 points and will involve either (a) replicating the results of an existing paper, and critically extending it further (if possible), or (b) presenting the results of original research. Typically the paper will be chosen by the student in consultation with the instructor and should have the following characteristics: (1) the paper must analyze a heterodox macro/pe/development question, and (2) the paper must use substantial time series econometric analysis, preferably from one of the large areas covered in this class: vector autoregression, cointegration analysis, state-space modeling. In addition to submitting it, students will be required to give a 20 minute presentation on their research paper during the exam week. 2

3 TENTATIVE SCHEDULE AND READINGS: Week 1: Preliminaries. Topics: conditional expectation, deterministic difference equations, lag operators. Chapter 1, Enders. Chapter 1, 2, Hamilton. Week 2-3: Univariate Stationary Time Series Models. Topics: stochastic difference equations, ARMA(p,q) models, Box-Jenkins modeling strategy. Chapter 3, Enders. Chapter 3, Hamilton. Week 4-5: Univariate Time Series Models with Trends. Topics: trends in time series, unit root testing, Monte Carlo experiments, regression with trending variables, structural change in time series. Chapter 4, Enders. Stock, J. H., and Watson, M. W Variable Trends in Economic Time Series. Journal of Economic Perspectives, 2(3): (read pp ) Chapter 15, 16, 17, Hamilton. Basu, D., and Manolakos, P. T Is There a Tendency for the Rate of Profit to Fall? Econometric Evidence for the U.S. Economy, Review of Radical Political Economics, 45(1): Hein, E. and C. Ochsen Regimes of Interest Rate, Income Shares, Savings and Investment: A Kaleckian Model and Empirical Estimations for Some Advanced OECD Countries. Metroeconomica, 54(4):

4 Matthews, P. H An Econometric Model of the Circuit of Capital. Metroeconomica, 51(1):1-39. Week 6-8: Multivariate Stationary Time Series Models. Topics: intervention analysis, autoregressive distributed lag (ADL) and transfer function models, vector autoregressions. Chapter 5, Enders. Stock, J. H., and M. W. Watson Vector Autoregressions. Journal of Economic Perspectives, 15(4): Chapter 10, 11, Hamilton. Barbosa-Filho, N. H. and L. Taylor Distributive And Demand Cycles In The US Economy-A Structuralist Goodwin Model. Metroeconomica, 57(3): Basu, D., Chen, Y. and J. Oh Class Struggle and Economic Fluctuations: VAR Analysis of the post-war U.S. Economy. International Review of Applied Economics, 27(5): Blanchard, O. J., and Quah, D The Dynamic Effects of Demand and Supply Disturbances. American Economic Review, 79(4): Blanchard, O. J., and Perotti, R An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output. Quarterly Journal of Economics, 117(4): Caldara, D., and Kamps, C What are the effects of fiscal policy shocks? A VAR-based comparative analysis. Working Paper Series No. 877, European Central Bank. Dube, A., Kaplan, E., and Naidu, S Coups, Corporations and Classified Information. Quarterly Journal of Economics, 126(3): Hoffmann, A An Overinvestment Cycle in Central and Eastern Europe. Metroeconomica, 61(4): Kim, S., and Roubini, N Exchange rate anomalies in the industrial countries: A solution with a structural VAR approach. Journal of Monetary Economics, 42: Stockhammer, E., and O. Onaran Accumulation, Distribution and employment: A Structural VAR approach to a Kaleckian macro model. Structural Change and Economic Dynamics, 15:

5 Week 9-11: Cointegration and Error Correction. Topics: representation and analysis of cointegrated systems, Engle-Granger methodology, Johansen Methodology, ARDL bounds testing methodology. Chapter 6, Enders. Stock, J. H., and M. W. Watson Variable Trends in Economic Time Series. Journal of Economic Perspectives, 2(3): (read pp ) Chapter 19, 20, Hamilton. Murray, M. P A Drunk and Her Dog: An Illustration of Cointegration and Error Correction. The American Statistician, 48(1): Pesaran, H.M., Shin, Y., and Smith, R.J., Bounds testing approaches to the analysis of long-run relationships. Journal of Applied Econometrics, 16, Atkins, F. J., and Coe, P. J An ARDL bounds test of the long-run Fisher effect in the United States and Canada. Journal of Macroeconomics, 24: Azadeh, R., Chu, B. M., and Lavoie, M Linear and Non-Linear Granger Causality Between Short-Term and Long-Term Interest Rates: A Rolling Window Strategy. Metroeconomica. DOI: /meca Johansen, S. and Juselius, K Maximum Likelihood Estimation and Inference on Cointegration - with Applications to the Demand for Money. Oxford Bulletin of Economics and Statistics, 52(2): Heintz, J The impact of public capital on the US private economy: new evidence and analysis. International Review of Applied Economics, 24(5): Irandoust, M., and Ericsson, J Are exports and imports cointegrated? An international comparison. Metroeconomica, 55(1): Lopez, J., Sanchez, A., and A. Spanos Macroeconomic Linkages in Mexico. Metroeconomica, 62(2): Marquetti, A Do Rising Real Wages Increase The Rate Of Labor-Saving Technical Change? Some Econometric Evidence. Metroeconomica, 55(4):

6 Piovani, C Class Power and China s Productivity Miracle: Applying the Labour Extraction Model to China s Industrial Sector, Review of Radical Political Economics, 46: Sarich, J., and J. Hecht Competition and International Equity Returns: Some Empirical Tests of Turbulent Arbitrage. Review of Radical Political Economics, 42(1):pp Shaikh, A., and Antonopoulos, R Explaining long term exchange rate behavior in the United States and Japan. In Moudud, J.K., Bina, C., and Mason, P. (Eds.), Alternative Theories of Competition: Challenges to the Orthodoxy. New York: Routledge Week 12-13: State-Space Modeling. Topics: state-space representation, Kalman filter, Markov-switching models. Hamilton, J. D State-Space Models. Chapter 50, Handbook of Econometrics, Volume IV, Edited by R. F. Engle and D. L. McFadden. Elsevier Science. (This is available on MOODLE). Chapter 13, Hamilton. Chapter 6, Shumway and Stoffer. Meinhold, R. J. and Singpurwalla, N. D Understanding the Kalman Filter. The American Statistician, 37(2): Angeriz, A., and Arestis, P Has Inflation Targeting Had Any Impact on Inflation? Journal of Postkeynesian Economics, 28(4): Goldstein, J. P Predator-Prey Model Estimates of the Cyclical Profit Squeeze. Metroeconomica, 50(2): Lam, P A Markov-switching model of GNP growth with duration dependence. International Economic Review, 45(1): Stock, J. H., and M. W. Watson Variable Trends in Economic Time Series. Journal of Economic Perspectives, 2(3):