This study aimed to explain the factors that influenced an individual’s decision to migrate. The method of analysis in this study was the estimation of the probit regression model with data from the Indonesian Family Life Survey (IFLS-5), which covered 30,000 individuals from 13 provinces in Indonesia. Data from IFLS-5 were longitudinal data, meaning that the study was looking for data consistently to get reliable data from respondents. The research variables to determine the individual’s decision to migrate were education level, income level, employment status, marital status, land ownership status, health quality, gender, residence status, and poverty status. Individual decision to migrate as a dependent variable was placed as a dummy variable. The results showed that the level of education, income level, employment status, marital status, land ownership status, health quality, and poverty status significantly influenced an individual’s decision to migrate. Meanwhile, gender and residence status did not significantly affect an individual’s decision to migrate. This research recommends that it is necessary to pursue a policy of economic equality between regions because economic factors are the main trigger for an individual’s decision to migrate. Policies to overcome economic disparities among regions will reduce the individual’s decision to migrate.

The role of money in the modern economy highly determines the intensity and the development of the macroeconomy. The money supply is assumed to be as much as money demand, which reflects the economic character of a country and indicates the growth and development of macroeconomy. In Indonesia, the money supply (M1) is related to the economic dynamics in either the monetary market or the goods market. This research aims at analyzing factors that influence the money supply and to what extent the economic factors affect the money supply in Indonesia. The analysis method used in this research was Vector Autoregressive (VAR) with some variables, such as money supply (M1), interest rate, and Gross Domestic Product (GDP) from the 1st quarter of 2001 until the 1st quarter of 2013. The data collection method was in the form of data compilation from credible sources, such as Bank of Indonesia (BI), Central Bureau of Statistics (CBS), and International Financial Statistics (IFS). To obtain adequate analysis results, several tests were taken, such as unit-root test, Granger causality test, and optimal lag. VAR analysis formulates the correlation among independent variables, so it also sees the study of impulse response and matrix decomposition.