Rice Production Essay Example

financial pressure to farmers who were already facing increasing debts and decreasing income. Additionally, there was an average annual decline of 2.4 percent in the area allocated for rice production, which had previously remained steady in the latter half of the 1970s. These changes mainly impacted marginal, nonirrigated farms. As a result, in 1985, during the last year of the Marcos regime, the country imported 538,000 tons of rice.

In the late 1980s, rice imports saw a slight rise. However, a drought in 1990 led to a production decline of 1.5%, resulting in an estimated import of 400,000 tons of rice. In the future, it may be necessary to use the remaining domestic rice stock.

The purpose of this study is to assess the factors impacting rice production in the Philippines. The goal is to establish policies that promote sustainable rice production and ensure food security for the Filipino people.

II. Problem Statement and Analysis Objectives

This research aims to analyze the growth of Palay Production in the Philippines from the first semester of 1991 to the second semester of 2002. The analysis will explore how variables such as land size, rainfall levels, and technological advancements influence rice production. To address these concerns, we will answer the following questions:
1.

The question at hand is whether three variables have a significant effect on Palay Production. These variables include:
a) the area of land allotted for planting Palay,
b) the amount of rainfall, and
c) an unspecified variable.

The relationship between the advancement of technology, area of land allotted for planting palay, and the amount of rainfall on rice production is analyzed in this paper using a multiple linear regression model.

The equation used for analysis is PROD = b0 + b1AREA + b2RAIN + b3TECH, where PROD represents the volume of rice produced, AREA represents the area of land allotted for planting palay, RAIN represents the amount of rainfall, and TECH represents the advancement of technology in the agricultural sector. The significance level of each independent variable will be determined using t-statistic with parameter estimates (b). The coefficient values are estimated using Least Square Method with a 95 percent confidence level. Moreover, overall significance of these variables on the dependent variable will be assessed using f-statistic.

The study's results will be validated using R2, which determines the influence of variables on the dependent component. A significance level of 5 percent and 21 degrees of freedom (derived from deducting the number of observations by the number of independent variables) are used to validate the results. The hypothesis being tested is that variables such as area allotted for planting palay, amount of rainfall, and advancement of technology in the agricultural sector have no significant effect on rice production in the Philippines. The graphs show overlapping trends, except for a slowdown in rice production during 1998's second semester.

Conclusion

Population increase, limited land area, and slow technology advancement hinder sufficient rice production in the Philippines. Policies should be formulated to increase rice production. New technologies mainly required capital inputs, such as irrigated land and fertilizers.

Due to limited capital, implementing new technologies takes a long time. This scarcity exists on the supply side, but increased demand requires countries to boost their exports in order to meet growing domestic demand caused by increased supply. Consequently, continuous technological development is necessary for future growth

to be sustained. If this growth is not achieved, the impact of input growth will decrease over time, as already indicated by the estimated regression equation. However, it should be noted that future growth does not solely rely on this factor.

In order to fully benefit from new techniques, a smooth flow of necessary resources into agriculture is necessary.

Bibliography

1. Economic Development 8th edition, by Michael s. Todaro and Stephen C. Smith, page 418-454 Agricultural Statistics c/o San Beda College Prof. Harold Glenn Valera