## ---------------------------------------------------------------------------- ## Grunfeld (1958) ## ## data ## availability: printed ## firms: General Motors, General Electric, US Steel, Atlantic Refining, ## Union Oil, Diamond Match, Goodyear, American Steel, ## Chrysler, IBM, Westinghouse ## errors: none (by definition) ## ## analysis ## result: mostly minor variations re last digit, ## General Motors: slopes and one s.e. (capital) are in error. ## Reasons unclear. ## Macro regression: discrepancies for all coef.s and se.s, ## presumably due to discrepancies for GM. ## ---------------------------------------------------------------------------- ## preliminaries source("start.R") ## data pre-processing gr8 <- subset(Grunfeld, firm %in% c("General Motors", "General Electric", "US Steel", "Atlantic Refining", "Union Oil", "Diamond Match", "Goodyear", "American Steel")) gr8$firm <- factor(gr8$firm) pgr8 <- plm.data(gr8, c("firm", "year")) gr3 <- subset(Grunfeld, firm %in% c("IBM", "Chrysler", "Westinghouse")) gr3$firm <- factor(gr3$firm) pgr3 <- plm.data(gr3, c("firm", "year")) # Table 25, p. 132 (constant terms not given) lm_GM <- lm(invest ~ value + capital, data = gr8, subset = firm == "General Motors") lm_GE <- lm(invest ~ value + capital, data = gr8, subset = firm == "General Electric") lm_US <- lm(invest ~ value + capital, data = gr8, subset = firm == "US Steel") lm_AR <- lm(invest ~ value + capital, data = gr8, subset = firm == "Atlantic Refining") lm_UO <- lm(invest ~ value + capital, data = gr8, subset = firm == "Union Oil") lm_DM <- lm(invest ~ value + capital, data = gr8, subset = firm == "Diamond Match") lm_GY <- lm(invest ~ value + capital, data = gr8, subset = firm == "Goodyear") lm_AS <- lm(invest ~ value + capital, data = gr8, subset = firm == "American Steel") gsummary(lm_GM) gsummary(lm_GE) gsummary(lm_US) gsummary(lm_AR) gsummary(lm_UO) gsummary(lm_DM) gsummary(lm_GY) gsummary(lm_AS) ## alternatively sf8 <- systemfit(invest ~ value + capital, method = "OLS", data = pgr8) gsummary(sf8) ## Macro regression (Table 25, col. "Aggr.") gr8_macro <- aggregate(gr8[,-4], list(gr8$year), sum)[,-1] lm_macro <- lm(invest ~ value + capital, data = gr8_macro) gsummary(lm_macro) ## Table 30, p. 148 (constant terms not given) ## R^2s in Table 29, p. 146 lm_IBM <- lm(invest ~ value + capital, data = gr3, subset = firm == "IBM") lm_CH <- lm(invest ~ value + capital, data = gr3, subset = firm == "Chrysler") lm_WH <- lm(invest ~ value + capital, data = gr3, subset = firm == "Westinghouse") gsummary(lm_IBM) gsummary(lm_CH) gsummary(lm_WH) ## alternatively sf3 <- systemfit(invest ~ value + capital, method = "OLS", data = pgr3) gsummary(sf3) ## aggregate regression using Grunfeld's Table 10 (Appendix), p. 164 ## very different from gsummary(lm_macro) lm_agg <- lm(invest ~ value + capital, data = Grunfeld_agg) gsummary(lm_agg)