Canova, Fabio, "Statistical Inference in Calibrated Models", Journal of Applied Econometrics, Vol. 9, Supplement, 1994, pp. S123-S144. Since most of the paper is methodological, I did not use any data set in the article. Instead, I employed estimates of the moments of interest from published work. For the first example of section 5, I simply use the benchmark numbers for mean and standard deviations of the equity premium and the risk free rate reported in Mehra and Prescott (1985). In the second example of section 5, given the parameter estimates of Eichenbaum (1991), I calculate what the variance of the actual output series should be so that lamba=0.8 and use that as benchmark to compare simulations. To make sure that the estimated variance of the output series is reasonable, I check it against the following industrial production series which I took from the citibase tape. date IP, base 1976. 7301 91.800 7302 93.100 7303 93.100 7304 93.400 7305 93.800 7306 94.500 7307 95.100 7308 95.100 7309 95.800 7310 96.100 7311 96.200 7312 94.700 7401 93.300 7402 93.000 7403 93.400 7404 93.200 7405 94.300 7406 94.600 7407 94.200 7408 93.900 7409 94.200 7410 93.600 7411 90.900 7412 87.100 7501 84.800 7502 83.500 7503 82.000 7504 82.700 7505 82.500 7506 83.600 7507 84.100 7508 85.600 7509 86.400 7510 86.900 7511 87.700 7512 88.400 7601 89.300 7602 90.900 7603 90.700 7604 91.100 7605 92.100 7606 92.200 7607 92.700 7608 93.200 7609 93.500 7610 93.900 7611 95.400 7612 96.200 7701 96.500 7702 97.200 7703 98.000 7704 99.000 7705 99.600 7706 100.400 7707 100.700 7708 101.000 7709 101.400 7710 101.800 7711 102.100 7712 102.100 7801 101.600 7802 101.600 7803 103.000 7804 105.500 7805 105.800 7806 106.900 7807 107.500 7808 107.700 7809 108.300 7810 109.200 7811 109.900 7812 110.800 7901 110.300 7902 110.900 7903 111.200 7904 109.900 7905 110.900 7906 110.900 7907 110.500 7908 110.200 7909 110.400 7910 111.000 7911 111.000 7912 111.000 8001 111.300 8002 111.400 8003 111.400 8004 109.100 8005 106.200 8006 105.000 8007 104.800 8008 106.300 8009 107.700 8010 108.500 8011 110.700 8012 111.000 8101 111.000 8102 111.200 8103 111.600 8104 110.600 8105 111.200 8106 112.000 8107 113.400 8108 112.800 8109 111.500 8110 110.400 8111 109.000 8112 107.400 8201 105.400 8202 107.000 8203 105.800 8204 104.500 8205 103.600 8206 103.000 8207 102.500 8208 102.000 8209 101.300 8210 100.500 8211 100.600 8212 100.500 8301 102.500 8302 103.300 8303 104.200 8304 105.600 8305 106.900 8306 107.800 8307 109.800 8308 111.600 8309 113.700 8310 114.400 8311 114.800 8312 115.500 8401 118.500 8402 119.300 8403 119.900 8404 120.500 8405 121.000 8406 121.900 8407 122.800 8408 123.000 8409 122.400 8410 122.100 8411 122.700 8412 122.700 8501 122.400 8502 122.900 8503 123.300 8504 123.100 8505 123.700 8506 123.500 8507 123.400 8508 124.100 8509 124.400 8510 123.700 8511 124.800 8512 125.400 8601 126.400 8602 125.500 8603 123.900 8604 124.700 8605 124.300 8606 124.100 8607 124.800 8608 124.900 8609 124.500 8610 125.300 8611 125.700 8612 126.800 8701 126.200 8702 127.100 8703 127.400 8704 127.400 8705 128.200 8706 129.100 8707 130.600 8708 131.200 8709 131.000 8710 132.500 8711 133.200 8712 133.900