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The analysis of Klein`s model „ The economic fluctuations in the United States 1921-1941” (1950)

The analysis of Klein`s model „ The economic fluctuations in the United States 1921-1941” (1950). Prepared by: Aleksander Rzewuski Roman Gąsowski. Few words about Lawrence R. Klein . born in 1920 in Omaha, Nebraska in Jewish family

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The analysis of Klein`s model „ The economic fluctuations in the United States 1921-1941” (1950)

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  1. The analysis of Klein`s model„ The economic fluctuations in the United States 1921-1941” (1950) Prepared by: Aleksander Rzewuski Roman Gąsowski

  2. Few words about Lawrence R. Klein • born in 1920 in Omaha, Nebraska in Jewish family • 1947 the book The Keynesian Revolution established him as one of the foremost scholars on Keynesian economics • In 1980 he was awarded the Nobel Memorial Prize in Economic Sciences

  3. The goal of our presentation • Introduction of Klein’s model • Estimation for data covering American economy in the period of 1921-1941 • Analysis of the results • Estimation of the model for contemporary data (1970-2000) • Comparison and final conclusions

  4. Background for Klein’s model • One of the first models to explain the economy as a whole • Published in 1950 • It includes years of Great Depression till the beginning of American participation in World War II • All variables are measured in billions of dollars

  5. Structural form of the model • Endogenous variables of the model are: • Consumption – Ct • Wages in private sector – Wp • Investments – It • Capital stock – Kt • GNP – Xt • Profits in private sector – Pt

  6. Structural form (cont’d) • Exogenous variables are: • Government expenditure – Gt • Wages in public sector – Wg • Taxes – Tt • Lagged variables: Pt-1, Kt-1, Xt-1

  7. Equations of the model • Ct= α1 + α2Pt+ α3Pt-1 + α4 (Wp+Wg) + u1t • Wp= γ1 + γ2Xt+ γ3Xt-1 + γ4t + u3t • It= β1 + β2Pt+ β3Pt-1 + β4Kt-1 + u2t • Kt= It+ Kt-1 • Xt= Ct+ It+ Gt • Pt= Xt–Wp– Tt

  8. Three-stage least squares regression • ---------------------------------------------------------------------- • Equation Obs Parms RMSE "R-sq" chi2 P • ---------------------------------------------------------------------- • c 21 3 .9443305 0.9801 864.59 0.0000 • wp 21 3 .7211282 0.9863 1594.75 0.0000 • i 21 3 1.446736 0.8258 162.98 0.0000 • ---------------------------------------------------------------------- • ------------------------------------------------------------------------------ • | Coef. Std. Err. z P>|z| [95% Conf. Interval] • -------------+---------------------------------------------------------------- • c | • p | • L1 | .1631439 .1004382 1.62 0.104 -.0337113 .3599992 • -- | .1248904 .1081291 1.16 0.248 -.0870387 .3368194 • wp_plus_wg | .790081 .0379379 20.83 0.000 .715724 .8644379 • _cons | 16.44079 1.304549 12.60 0.000 13.88392 18.99766 • -------------+---------------------------------------------------------------- • wp | • x | • -- | .4004919 .0318134 12.59 0.000 .3381388 .462845 • L1 | .181291 .0341588 5.31 0.000 .1143411 .2482409 • year | .149674 .0279352 5.36 0.000 .094922 .2044261 • _cons | -287.2233 53.4488 -5.37 0.000 -391.9811 -182.4656 • -------------+---------------------------------------------------------------- • i | • p | • -- | -.0130791 .1618962 -0.08 0.936 -.3303898 .3042316 • L1 | .7557238 .1529331 4.94 0.000 .4559805 1.055467 • k1 | -.1948482 .0325307 -5.99 0.000 -.2586072 -.1310893 • _cons | 28.17785 6.793768 4.15 0.000 14.86231 41.49339 • ------------------------------------------------------------------------------ • Endogenous variables: c wp i wp_plus_wg x p • Exogenous variables: L.p L.x year k1 g wg t • ------------------------------------------------------------------------------

  9. Interpretation • Estimates of all parameters look very reasonable • The point estimates are not sufficient • The signs of the parameter seem to be expectable in the context of economic theory • Most of the coefficients are significant] • Coefficient of determination (R2) for all equations is very high

  10. As many economists pointed out the model does not track the historical data well However it can be used to simulate various policies Observed level of GNP (solid line), simulated level of GNP (dotted line)

  11. Possible way of policy simulation • Change the value of government expenditure in one year holding all other levels of g and all other variables fixed • Run the estimation with altered data and compare new „under shock” values of GNP with those obtained before • Observe the difference in GNP and conclude policy recommendation

  12. Analogous analysis of contemporary data • Data set covers the period of 1970 – 2000 • The data were gathered from World Development Indicators database and from Bureau of Economic Analysis of U.S. Department of Commerce • All variables are measured in billions of dollars

  13. Three-stage least squares regression • ---------------------------------------------------------------------- • Equation Obs Parms RMSE "R-sq" chi2 P • ---------------------------------------------------------------------- • c 30 3 76.55733 0.9982 21791.42 0.0000 • wp 30 3 52.79923 0.9973 12318.64 0.0000 • i 30 3 22.7667 0.9179 322.08 0.0000 • ---------------------------------------------------------------------- • ------------------------------------------------------------------------------ • | Coef. Std. Err. z P>|z| [95% Conf. Interval] • -------------+---------------------------------------------------------------- • c | • p | • L1 | -1.976323 .6102105 -3.24 0.001 -3.172313 -.7803319 • -- | 2.711593 .6818255 3.98 0.000 1.37524 4.047946 • wp_plus_wg | 1.312336 .0587717 22.33 0.000 1.197146 1.427527 • _cons | -186.1593 28.9765 -6.42 0.000 -242.9522 -129.3664 • -------------+---------------------------------------------------------------- • wp | • x | • -- | 1.123226 .1578403 7.12 0.000 .813865 1.432588 • L1 | -.6039088 .1601588 -3.77 0.000 -.9178143 -.2900034 • year | -45.23511 7.061766 -6.41 0.000 -59.07592 -31.3943 • _cons | 89054.35 13910.47 6.40 0.000 61790.33 116318.4 • -------------+---------------------------------------------------------------- • i | • p | • -- | .0512894 .3611802 0.14 0.887 -.6566108 .7591897 • L1 | .4434355 .4515954 0.98 0.326 -.4416753 1.328546 • k1 | -.130268 .069566 -1.87 0.061 -.2666149 .006079 • _cons | 17.08937 10.72621 1.59 0.111 -3.933628 38.11236 • ------------------------------------------------------------------------------ • Endogenous variables: c wp i wp_plus_wg x p • Exogenous variables: L.p L.x year k1 g wg t • ------------------------------------------------------------------------------

  14. Interpretation • Coefficient of determination (R2) is even higher • Most of the parameters are significant at the level of 1% • Model tracks the economy indicators well

  15. Final conclusions • Both models follow the reality well • Do they give any predictions? • Only policy simulation • Pioneer work and the cornerstone in the evolution of econometrics

  16. THANK YOU

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