# Multiple regression model in SPSS.

Problem 1: In an earlier assignment, you estimated a simple t-test to ascertain if IMF lending programs in Latin America served to attract or deter foreign direct investment.

Of course, the principal problem with this result is that we really can't say much definitively because we don't control for alternative explanations. Using the following dataset (lat_am_cap_flows_example_MR.sav), run a multiple regression on FDI flows using the following independent variables: selected, lgnppc (per capita GNP), lgrowth (growth) and lgnpmd (GNP in millions of US dollars).

Interpret the intercept and all other coefficients, the model significance, and r-squared. Using these findings, what can we say substantively? Is it the case that IMF programs attract foreign direct investment or deter it? How much do IMF programs matter?

Problem 2: A recurring example in class has been the effects of trade on levels of government expenditure. Using the following dataset (govexpend_MR_example2.sav), compute a multiple regression of government expenditure using the following independent variables: gdpgrowth (growth rate), loggdppc (GDP per capita), pctpop65 (% of the population 65 or older), tradegdp (trade as a percentage of GDP) and election (a dummy variable for whether or not there was a national election during the year).

Interpret the intercept and all other coefficients, the model significance, and r-squared. Using these findings, what can we say substantively? How much does trade matter? Does this finding support the race to the bottom argument?

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