00000cab a22000004cb4500 IPP-00000284491 IPP 20190502103751.0 190502s2011 xx d | ||r |||||eng|| eng Mapa, Dennis S. Agricultural output and the states of poverty in the Philippines Evidence from self-rated poverty data 2011 The high poverty incidence in the country is a major development concern that needs to be addressed by our policy makers. Official poverty data shows that headcount poverty increased to 26.5% of the total population in 2009 from 26.4% in 2006. The number of poor Filipinos reached 23 million in 2009. Since poverty incidence has dynamic patters, studies using official poverty data encounter difficulty because of limited number of data points. This study builds econometric models in analyzing the movement of poverty in the country using the quarterly self-rated poverty series of the Social Weather Stations. The first model uses a Markov Switching model to determine the states of poverty. The model assumes two states: extremely high and high poverty states. An average of 61% of the population considered themselves as poor when the country is in the state of extremely high poverty. In times of high poverty, an average of 49.5% of the population considered themselves as poor. The results showed that once the country is in the state of extremely high poverty, it stays there for an average of 24 quarters or six years before moving out. The paper then used the Logistic Regression model to show what determines the states of poverty. Three variables are considered as important determinants: agricultural output, government spending and underemployment rate. A one-percentage point increase in agricultural output reduces the probability of being in the extremely high state of poverty by about 46 percentage points, all things being the same. The study shows that poverty incidence in the country is dynamic and frequent monitoring through self-related poverty surveys, perhaps at the provincial level, is important in order to assess the effectiveness of the government programs in reducing poverty. The self-rated poverty surveys can complement the official statistics on poverty incidence. Poverty Lucagbo, Michel Daniel C. Garcia, Heavenly Joy P. Transactions of the National Academy of Science and Technology Vol. 33, no. 1 (Jul. 2011), 217 UPD DMLP Article FI