Openness, Technological Change and Labor Demand in Pre-Crisis Indonesia.

This paper examines the impact of export orientation, import competition, foreign ownership and the rate of capital accumulation on the relative demand for skilled and unskilled labor in pre-crisis Indonesia.TRADE ; COMPETITION ; LABOUR MARKET

The Chronic Poor, the Transient Poor, and the Vulnerable in Indonesia Before and After the Crisis

Using cross-section data from household surveys, we estimate several categories of household poverty and vulnerability in Indonesia by combining the available information on current consumption levels, estimates of vulnerability to poverty, and estimates of expected consumption levels. the results indicate that the level of vulnerability to poverty among Indonesian households after the crisis unambiguously increased from pre-crisis levels. furthermore, not only did the poverty rate in Indonesia increase significantly because of the crisis, but also much of this increase was due to an increase in chronic poverty. likewise, the number of households that have high vulnerability to poverty has almost tripled. as a result, the total number of households in the vulnerable category has jumped from 18 percent of the population in 1996 to more than one third of the population in 1999. *we thank shubham chauduri and john maxwell for valuable comments and suggestions and daniel perwira and wenefrida widyanti for excellent research assistance. we are grateful to statistics Indonesia (bps) for providing access to the data

The Impact of Private Sector Growth on Poverty Reduction: Evidence From Indonesia

This paper assesses the effect of public and private sector growth on poverty in Indonesia. we use fixed capital formation growth as the proxy for the private sector and growth in government spending as the indicator of the public sector. we find that growth in both sectors significantly reduces poverty; moreover, they have the same elasticity. therefore, growth in both public and private sector spending will reduce poverty twice as fast as just relying on public spending. the implication is that it is crucial for governments to improve the business climate in their countries so that the private sector will be able to flourish and in the end expedite poverty reduction. keywords: private sector; investment; government expenditure; poverty reduction; Indonesia jel classification: h50, i32, o4

The Impact of Rising Inequality on Growth and Unemployment in Indonesia: What Does the Evidence Say?

Consumption inequality has been rising in Indonesia over the last decade (see Figure 1). Before the onset of the Asian financal crisis (AFC) in 1997, Indonesia experienced little change in inequality. From 1980 to 1996, the Gini ratio (a standard economic measure of inequality), based on household consumption, fluctuated between 0.32 and 0.36.1 While the impact of the AFC brought down inequality to Indonesia's lowest level since 1980 (0.30 in 2000), this was largely because the crisis hit those who were relatively well-off in urban areas harder than it hit Indonesia's poor in rural areas. However, since recovering from the AFC in the early 2000s, the Gini ratio has increased rapidly and has reached new records of 0.41 in 2011 and 2012. Of course, rising inequality is not restricted to Indonesia; there is growing concern about the current trend of rising inequality across the world.2 Nonetheless, while some argue that inequality in income or consumption is necessary for the accumulation of assets or market incentive for long-term growth investment, our research3 finds that increasing inequality will actually lead to adverse growth. Consumption inequality is usually closely related to other forms of inequality, such as inequality in access to education, health, and public services. This often manifests as inequality of opportunity. These dimensions of inequality have significant detrimental effects on economic growth, and even political and social stability. Thus, in turn, it also poses substantial risk to human development

The Implications of Poverty Dynamics for Targeting the Poor: Simulations Using Indonesian Data

One of the key challenges on delivering benefits of poverty programs to the poor is to ensure that the beneficiaries of the programs are indeed the targeted population. this paper aims at assessing the implications of poverty dynamics on the accuracy of targeting, using a three-year panel data from Indonesia. we find that the existence of poverty dynamics within only three years period already contributes to large inclusion and exclusion errors in program targeting. we simulate several scenarios as an alternative way to increase targeting accuracy by increasing the threshold for determining the program beneficiaries. we find that the higher the threshold, the exclusion error becomes lower but the inclusion error becomes larger. at the same time, the number of beneficiaries becomes larger, implying increasing program costs. however, a significant part of inclusion error is consisted of vulnerable households, which experience poverty in other years. these findings imply that if the government wants to make sure that the poor receive the benefits of poverty programs, they need to increase the budget allocated toward poverty programs substantially. this may require an integration of various existing poverty programs. another implication from the findings of this study points to the importance of regular and more frequent updating of the poor population database which is used for targeting of poverty programs. keywords: poverty, vulnerability, dynamics, targeting, Indonesi

Determining Comprehensive Criteria and Census Variables for the Protection of the Poor at the Local Level

The development of targeting methods for government social programs has to date experienced favorable progress. however, since the issuance of law no. 52/2009, there has been a shift from household-based targeting to family-based targeting. this paper offers an alternative method to determine a set of comprehensive criteria for family-based targeting. to establish the criteria, an analysis of locally-specific welfare indicators are undertaken. these indicators are used to determine levels of family welfare categories. the categories are set based on a number of variables which weigh the highest. these main variables may vary among regions. the levels of family welfare are determined through descriptive analysis and principal component analysis (pca). the levels defined are used for program recipient targeting based on the budget allocation for a region. the result of the analysis can be used for better targeting based on program clusters, such as education or health, in a given area. keywords: family, welfare, criteria, targeting, welfare level