% US county-level growth data set from Christoper H. Wheeler % Journal of Applied Econometrics web site, Jim LeSage added % the latitude/longitudes % Variables appear in the following order: % columns % 1 STATE/county = state FIPS code % 2 latitude centroid for the county % 3 longitude centroid for the county % 4 EMPGR = employment growth rate (1980-90) % 5 POPGR = population growth rate (1980-90) % 6 DEMPGR = employment growth rate minus % mean across all counties in same state (1980-90) % 7 DPOPGR = population growth rate minus % mean across all counties in same state (1980-90) % 8 LOGEMP = natural logarithm of employment 1980 % 9 LOGPOP = natural logarithm of population 1980 % 10 EDENS = employment density (employment per square mile) 1980 % 11 PDENS = population density (population per square mile) 1980 % 12 LOGAREA = natural logarithm of land area 1980 % 13 COLLRATE = fraction of adult population with bachelor's degree % or more 1980 % 14 MFGRATE = fraction of employment in manufacturing 1980 % 15 UR = unemployment rate 1980 % 16 PCINC = per capita income (dollars) 1979 % 17 EDUCSH = share of local government spending on education 1982 % 18 HWSH = share of local government spending on highways 1982 % 19 POLSH = share of local government spending on police 1982 % 20 NWRATE = fraction of population that is not white 1980 % 21 URBAN = urban indicator variable % (= 1 if county located in metropolitan area) 1990 % 22 RURAL = rural indicator variable % ( = 1 if county located outside metropolitan area) 1990 % load countyg.dat; y1 = countyg(:,4); % county employment growth rate y2 = countyg(:,5); % county population growth rate % latt = countyg(:,2); % long = countyg(:,3); % [j W j] = xy2cont(latt,long); n = length(y1); xmat = [ones(n,1) countyg(:,8) countyg(:,10:end-1)]; vnames = strvcat('y=empgr80-90','constant','logy80','empdensity','popdensity','log area', ... 'college','manufemp','unemploy','y-percapita','education spending','highway spending','police spending', ... 'non-white','urban dummy'); % employment growth regressions result1 = ols(y1,xmat); prt(result1,vnames); % population growth regressions result2 = ols(y2,xmat); prt(result2,vnames);