References

Prescribed text

1.

Johnston, J., and DiNardo, J. (1997), Econometric Methods (4th ed.), New York, McGraw-Hill.

Recommended texts

1.

Davidson, R., and MacKinnon, J. G. (2004), Econometric Theory and Methods, New York, Oxford University Press.

2.

Greene, W. H. (2018), Econometric Analysis (8th ed.), New York, Pearson.

3.

Hayashi, F. (2000), Econometrics, Princeton, Princeton University Press.

4.

Wooldridge, J. M. (2010), Econometric Analysis of Cross Section and Panel Data (2nd ed.), Cambridge, MA, MIT Press.

Software

1.

Kleiber, C., and Zeileis, A. (2008), Applied Econometrics with R, New York, Springer.

2.

R Core Team, R: A Language and Environment for Statistical Computing, Vienna, R Foundation for Statistical Computing, https://www.R-project.org.

Further reading

1.

Aitken, A. C. (1935), On least squares and linear combination of observations, Proceedings of the Royal Society of Edinburgh, 55, 42–48.

2.

Anderson, T. W., and Hsiao, C. (1981), Estimation of dynamic models with error components, Journal of the American Statistical Association, 76, 598–606.

3.

Anderson, T. W., and Rubin, H. (1949), Estimation of the parameters of a single equation in a complete system of stochastic equations, Annals of Mathematical Statistics, 20, 46–63.

4.

Angrist, J. D. (1990), Lifetime earnings and the Vietnam era draft lottery: evidence from Social Security administrative records, American Economic Review, 80, 313–336.

5.

Angrist, J. D., and Krueger, A. B. (1991), Does compulsory school attendance affect schooling and earnings?, Quarterly Journal of Economics, 106, 979–1014.

6.

Angrist, J. D., and Pischke, J.-S. (2009), Mostly Harmless Econometrics, Princeton, Princeton University Press.

7.

Anscombe, F. J. (1973), Graphs in statistical analysis, The American Statistician, 27, 17–21.

8.

Arellano, M., and Bond, S. (1991), Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations, Review of Economic Studies, 58, 277–297.

9.

Belsley, D. A., Kuh, E., and Welsch, R. E. (1980), Regression Diagnostics, New York, Wiley.

10.

Blundell, R., and Bond, S. (1998), Initial conditions and moment restrictions in dynamic panel data models, Journal of Econometrics, 87, 115–143.

11.

Bollerslev, T. (1986), Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31, 307–327.

12.

Bound, J., Jaeger, D. A., and Baker, R. M. (1995), Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak, Journal of the American Statistical Association, 90, 443–450.

13.

Box, G. E. P., and Jenkins, G. M. (1976), Time Series Analysis: Forecasting and Control (revised ed.), San Francisco, Holden-Day.

14.

Breusch, T. S. (1978), Testing for autocorrelation in dynamic linear models, Australian Economic Papers, 17, 334–355.

15.

Breusch, T. S., and Pagan, A. R. (1979), A simple test for heteroscedasticity and random coefficient variation, Econometrica, 47, 1287–1294.

16.

Breusch, T. S., and Pagan, A. R. (1980), The Lagrange multiplier test and its applications to model specification in econometrics, Review of Economic Studies, 47, 239–253.

17.

Cameron, A. C., and Trivedi, P. K. (2013), Regression Analysis of Count Data (2nd ed.), Cambridge, Cambridge University Press.

18.

Chow, G. C. (1960), Tests of equality between sets of coefficients in two linear regressions, Econometrica, 28, 591–605.

19.

Cochrane, D., and Orcutt, G. H. (1949), Application of least squares regression to relationships containing auto-correlated error terms, Journal of the American Statistical Association, 44, 32–61.

20.

Dickey, D. A., and Fuller, W. A. (1979), Distribution of the estimators for autoregressive time series with a unit root, Journal of the American Statistical Association, 74, 427–431.

21.

Durbin, J. (1954), Errors in variables, Review of the International Statistical Institute, 22, 23–32.

22.

Durbin, J. (1970), Testing for serial correlation in least-squares regression when some of the regressors are lagged dependent variables, Econometrica, 38, 410–421.

23.

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24.

Engle, R. F. (1982), Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 50, 987–1007.

25.

Engle, R. F., and Granger, C. W. J. (1987), Co-integration and error correction: representation, estimation, and testing, Econometrica, 55, 251–276.

26.

Frisch, R. (1933), Editor’s note, Econometrica, 1, 1–4.

27.

Fuller, W. A. (1976), Introduction to Statistical Time Series, New York, Wiley.

28.

Godfrey, L. G. (1978), Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables, Econometrica, 46, 1293–1301.

29.

Goldfeld, S. M., and Quandt, R. E. (1965), Some tests for homoscedasticity, Journal of the American Statistical Association, 60, 539–547.

30.

Gourieroux, C., Monfort, A., and Trognon, A. (1984), Pseudo maximum likelihood methods: applications to Poisson models, Econometrica, 52, 701–720.

31.

Granger, C. W. J. (1969), Investigating causal relations by econometric models and cross-spectral methods, Econometrica, 37, 424–438.

32.

Granger, C. W. J., and Newbold, P. (1974), Spurious regressions in econometrics, Journal of Econometrics, 2, 111–120.

33.

Haavelmo, T. (1943), The statistical implications of a system of simultaneous equations, Econometrica, 11, 1–12.

34.

Haavelmo, T. (1944), The probability approach in econometrics, Econometrica, 12 (Supplement), 1–118.

35.

Hansen, L. P. (1982), Large sample properties of generalized method of moments estimators, Econometrica, 50, 1029–1054.

36.

Hansen, L. P., and Singleton, K. J. (1982), Generalized instrumental variables estimation of nonlinear rational expectations models, Econometrica, 50, 1269–1286.

37.

Hansen, L. P., Heaton, J., and Yaron, A. (1996), Finite-sample properties of some alternative GMM estimators, Journal of Business and Economic Statistics, 14, 262–280.

38.

Harvey, A. C., and Durbin, J. (1986), The effects of seat belt legislation on British road casualties: a case study in structural time series modelling, Journal of the Royal Statistical Society, Series A, 149, 187–227.

39.

Hausman, J. A. (1978), Specification tests in econometrics, Econometrica, 46, 1251–1271.

40.

Hausman, J. A., and Taylor, W. E. (1981), Panel data and unobservable individual effects, Econometrica, 49, 1377–1398.

41.

Heckman, J. J. (1979), Sample selection bias as a specification error, Econometrica, 47, 153–161.

42.

Hendry, D. F., and Mizon, G. E. (1978), Serial correlation as a convenient simplification, not a nuisance: a comment on a study of the demand for money by the Bank of England, Economic Journal, 88, 549–563.

43.

Hildreth, C., and Lu, J. Y. (1960), Demand relations with autocorrelated disturbances, Technical Bulletin 276, Michigan State University Agricultural Experiment Station.

44.

Johansen, S. (1988), Statistical analysis of cointegration vectors, Journal of Economic Dynamics and Control, 12, 231–254.

45.

Koenker, R. (1981), A note on studentizing a test for heteroscedasticity, Journal of Econometrics, 17, 107–112.

46.

Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., and Shin, Y. (1992), Testing the null hypothesis of stationarity against the alternative of a unit root, Journal of Econometrics, 54, 159–178.

47.

Ljung, G. M., and Box, G. E. P. (1978), On a measure of lack of fit in time series models, Biometrika, 65, 297–303.

48.

MacKinnon, J. G. (1991), Critical values for cointegration tests, in R. F. Engle and C. W. J. Granger (eds.), Long-Run Economic Relationships, Oxford, Oxford University Press, 267–276.

49.

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50.

McFadden, D. (1974), Conditional logit analysis of qualitative choice behavior, in P. Zarembka (ed.), Frontiers in Econometrics, New York, Academic Press, 105–142.

51.

Mehra, R., and Prescott, E. C. (1985), The equity premium: a puzzle, Journal of Monetary Economics, 15, 145–161.

52.

Modigliani, F. (1966), The life cycle hypothesis of saving, the demand for wealth and the supply of capital, Social Research, 33, 160–217.

53.

Moulton, B. R. (1990), An illustration of a pitfall in estimating the effects of aggregate variables on micro units, Review of Economics and Statistics, 72, 334–338.

54.

Mundlak, Y. (1978), On the pooling of time series and cross section data, Econometrica, 46, 69–85.

55.

Nelson, C. R., and Plosser, C. I. (1982), Trends and random walks in macroeconomic time series, Journal of Monetary Economics, 10, 139–162.

56.

Newey, W. K., and West, K. D. (1987), A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix, Econometrica, 55, 703–708.

57.

Nickell, S. (1981), Biases in dynamic models with fixed effects, Econometrica, 49, 1417–1426.

58.

Osterwald-Lenum, M. (1992), A note with quantiles of the asymptotic distribution of the maximum likelihood cointegration rank test statistics, Oxford Bulletin of Economics and Statistics, 54, 461–472.

59.

Perron, P. (1989), The great crash, the oil price shock, and the unit root hypothesis, Econometrica, 57, 1361–1401.

60.

Phillips, P. C. B. (1986), Understanding spurious regressions in econometrics, Journal of Econometrics, 33, 311–340.

61.

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62.

Ramsey, J. B. (1969), Tests for specification errors in classical linear least-squares regression analysis, Journal of the Royal Statistical Society, Series B, 31, 350–371.

63.

Said, S. E., and Dickey, D. A. (1984), Testing for unit roots in autoregressive-moving average models of unknown order, Biometrika, 71, 599–607.

64.

Salem, A. B. Z., and Mount, T. D. (1974), A convenient descriptive model of income distribution: the gamma density, Econometrica, 42, 1115–1127.

65.

Sargan, J. D. (1958), The estimation of economic relationships using instrumental variables, Econometrica, 26, 393–415.

66.

Sims, C. A. (1980), Macroeconomics and reality, Econometrica, 48, 1–48.

67.

Staiger, D., and Stock, J. H. (1997), Instrumental variables regression with weak instruments, Econometrica, 65, 557–586.

68.

Stock, J. H. (1987), Asymptotic properties of least squares estimators of cointegrating vectors, Econometrica, 55, 1035–1056.

69.

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70.

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71.

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72.

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73.

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74.

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75.

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