Panel Data Analysis in EViews

Crime and deterrence, US NC counties 1981-87Example 13.9 and problem 14.7 (using crime4.wf1)

structure the databes (identify i and t) (but do not let EViews balance anything unless you explicitly want

that)

Pooled OLS, clustered errors

log(crimeit) = β’xit+ uit

Cov(xit, uit) = 0

Dependent Variable: LOG(CRMRTE) Method: Panel Least Squares Sample: 1981 1987 Cross-sections included: 90 White cross-section standard errors & covariance (d.f. corrected)

Variable Coefficient Std. Error t-Statistic Prob.

C -2.206729 0.196612 -11.22375 0.0000 LOG(PRBARR) -0.721511 0.023373 -30.86915 0.0000

LOG(PRBCONV) -0.549277 0.025941 -21.17440 0.0000 LOG(PRBPRIS) 0.237972 0.055093 4.319484 0.0000 LOG(AVGSEN) -0.065201 0.024699 -2.639795 0.0085 LOG(POLPC) 0.362523 0.024715 14.66827 0.0000

County fixed-effects, iid errors

Dependent Variable: LOG(CRMRTE) Method: Panel Least Squares Sample: 1981 1987 Cross-sections included: 90

Variable Coefficient Std. Error t-Statistic Prob.

C -1.872858 0.172931 -10.83007 0.0000 LOG(PRBARR) -0.383537 0.033467 -11.46009 0.0000

LOG(PRBCONV) -0.305976 0.021858 -13.99847 0.0000 LOG(PRBPRIS) -0.195451 0.033364 -5.858201 0.0000 LOG(AVGSEN) 0.035664 0.026125 1.365157 0.1728 LOG(POLPC) 0.413771 0.027469 15.06334 0.0000

Effects Specification

Cross-section fixed (dummy variables)

log(crimeit) = β’xit+ ai+ vit

Cov(xit, ai) ≠ 0

Cov(xit, vis) = 0

County random effects, iid errors

Dependent Variable: LOG(CRMRTE) Method: Panel EGLS (Cross-section random effects) Sample: 1981 1987 Cross-sections included: 90 Swamy and Arora estimator of component variances

Variable Coefficient Std. Error t-Statistic Prob.

C -1.929440 0.167097 -11.54681 0.0000 LOG(PRBARR) -0.448597 0.030760 -14.58367 0.0000

LOG(PRBCONV) -0.346917 0.020209 -17.16632 0.0000 LOG(PRBPRIS) -0.187692 0.032802 -5.722010 0.0000 LOG(AVGSEN) 0.027629 0.025909 1.066421 0.2866 LOG(POLPC) 0.418481 0.025433 16.45441 0.0000

Effects Specification Cross-section random S.D. / Rho 0.299778 0.8065

Idiosyncratic random S.D. / Rho 0.146818 0.1935

log(crimeit) = β’xit+ ai+ vit

Cov(xit, ai) = 0

Cov(xit, vis) = 0

County & year FE, iid errors

Dependent Variable: LOG(CRMRTE) Method: Panel Least Squares Sample: 1981 1987 Cross-sections included: 90

Variable Coefficient Std. Error t-Statistic Prob.

C -1.663947 0.165974 -10.02535 0.0000 LOG(PRBARR) -0.359794 0.032419 -11.09819 0.0000

LOG(PRBCONV) -0.285873 0.021217 -13.47359 0.0000 LOG(PRBPRIS) -0.182781 0.032461 -5.630777 0.0000 LOG(AVGSEN) -0.004488 0.026447 -0.169694 0.8653 LOG(POLPC) 0.424114 0.026366 16.08559 0.0000

Effects Specification

Cross-section fixed (dummy variables) Period fixed (dummy variables)

log(crimeit) = β’xit+ ai+ dt + wit

Cov(xit, ai) ≠ 0

Cov(xit, dt) ≠ 0

Cov(xit, wis) = 0

County & year FE, cluster errors

Dependent Variable: LOG(CRMRTE) Method: Panel Least Squares Sample: 1981 1987 Cross-sections included: 90 White cross-section standard errors & covariance (d.f. corrected)

Variable Coefficient Std. Error t-Statistic Prob.

C -1.663947 0.328918 -5.058854 0.0000 LOG(PRBARR) -0.359794 0.037349 -9.633410 0.0000

LOG(PRBCONV) -0.285873 0.042916 -6.661205 0.0000 LOG(PRBPRIS) -0.182781 0.032330 -5.653590 0.0000 LOG(AVGSEN) -0.004488 0.042343 -0.105989 0.9156 LOG(POLPC) 0.424114 0.065212 6.503644 0.0000

Effects Specification Cross-section fixed (dummy variables)

Period fixed (dummy variables)

log(crimeit) = β’xit+ ai+ dt + wit

Cov(xit, ai) ≠ 0

Cov(xit, dt) ≠ 0

Cov(xit, wis) = 0

County FD & year FE, cluster errors

Δlog(crimeit) = β’Δxit+ Δdt + Δwit

Cov(xit, dt) ≠ 0

Cov(xit, wis) = 0

Dependent Variable: D(LOG(CRMRTE)) White cross-section standard errors & covariance (d.f. corrected)

Variable Coefficient Std. Error t-Statistic Prob.

C -0.006299 0.000701 -8.988490 0.0000 D(LOG(PRBARR)) -0.327494 0.030836 -10.62060 0.0000

D(LOG(PRBCONV)) -0.238107 0.038689 -6.154312 0.0000 D(LOG(PRBPRIS)) -0.165046 0.018626 -8.861234 0.0000 D(LOG(AVGSEN)) -0.021761 0.023078 -0.942913 0.3462 D(LOG(POLPC)) 0.398426 0.048313 8.246702 0.0000

Effects Specification Period fixed (dummy variables)

Summary of results

OLS + cluster

Cty FE Cty RE Cty+Y FE Cty+Y FE + cluster

Cty FD +Y FE + cluster

log(prbarr) -0.722 -0.384 -0.449 -0.360 -0.360 -0.327 (6.59)** (11.46)** (13.74)** (11.10)** (6.05)** (5.80)**

log(prbconv) -0.549 -0.306 -0.347 -0.286 -0.286 -0.238 (7.80)** (14.00)** (16.18)** (13.47)** (5.55)** (6.02)**

log(prbpris) 0.238 -0.195 -0.188 -0.183 -0.183 -0.165 (2.23)* (5.86)** (5.39)** (5.63)** (4.04)** (3.60)**

log(avgsen) -0.065 0.036 0.028 -0.004 -0.004 -0.022 (0.63) (1.37) (1.00) (0.17) (0.13) (0.84)

log(polpc) 0.363 0.414 0.418 0.424 0.424 0.398 (3.03)** (15.06)** (15.51)** (16.09)** (5.00)** (3.87)**

Observations 630 630 630 630 630 630 t statistics in parentheses * significant at 5%; ** significant at 1%