POVERTY AND ACCESS TO INFRASTRUCTURE IN PAPUA NEW GUINEA

In this paper, our overall goal is to understand how effective access to infrastructure is in reducing poverty in PNG. To meet this goal, we examine poverty in PNG, and seek to show the relationship between poverty and access to infrastructure and then identify the determinants of poverty. In our analysis, we test whether or not access to infrastructure is a significant factor in a household's poverty status. Finally, we want to understand what policies will be effective in overcoming poverty in PNG. Our results show that poverty in PNG is primarily rural and is associated with those in communities with poor access to services, markets, and transportation. Our simulations illustrate that improving access to school leads to large declines in poverty. Increasing access to poverty for those that are currently most isolated would have a significant effect in decreasing the severity of poverty.Food Security and Poverty, Public Economics,

IS IT BETTER TO BE A BOY? A DISAGGREGATED OUTLAY EQUIVALENT ANALYSIS OF GENDER BIAS IN PAPUA NEW GUINEA

Discrimination in the allocation of goods between boys and girls within households in Papua New Guinea is examined using Deatons (1989) outlay-equivalent ratio method. Adding a boy to the household reduces expenditure on adult goods by as much as would a nine-tenths reduction in total outlay per member, but girls have no effect on adult goods expenditure. The hypothesis of Haddad and Reardon (1993) that gender bias is inversely related to the importance of female labour in agricultural production is not supported. There is no evidence of bias against girls in the urban sector.Labor and Human Capital,

HOW ELASTIC IS CALORIE DEMAND? PARAMETRIC, NONPARAMETRIC, AND SEMIPARAMETRIC RESULTS FOR URBAN PAPUA NEW GUINEA

This paper seeks further evidence on the elasticity of calorie demand with respect to household resources. The case presented is for urban areas of Papua New Guinea, where just over one-half of the population appear to obtain less than the recommended amount of dietary energy. The relationship between per capita calorie consumption and per capita expenditure in urban areas of Papua New Guinea is not consistent with the view that income changes have negligible effects on nutrient intakes. The unconditional calorie demand elasticity is approximately 0.6 for the poorest half of the population, most of whom have less than the recommended 2000 calories per day available to them. Using parametric and semiparametric estimation to control for a wide range of other influences on calorie consumption does not materially reduce the size of the elasticity. Therefore, these results are not supportive of growth-pessimism and instead suggest that policies that increase urban household incomes will also act to reduce undernutrition.Food Consumption/Nutrition/Food Safety,

How widespread are non-linear crowding out effects? The response of private transfers to income in four developing countries

This paper investigates whether there is a non-linear relationship between income and the private transfers received by households in developing countries. If private transfers are unresponsive to household income, expansion of public social security and other transfer programs is unlikely to crowd out private transfers, contrary to concerns first raised by Barro and Becker. There is little existing evidence for crowding out effects in the literature, but this may be because they have been obscured by methods that ignore non-linearities. If donors switch from altruistic motivations to exchange motivations as recipient income increases, a sharp non-linear relationship between private transfers and income may result. In fact, threshold regression techniques find such non-linearity in the Philippines and after accounting for these there is evidence of serious crowding out, with 30 to 80 percent of private transfers potentially displaced for low-income households [Cox, Hansen and Jimenez 2004, 'How Responsiveare Private Transfers to Income?' Journal of Public Economics]. To see if these non-linear effects occur more widely, semiparametric and threshold regression methods are used to model private transfers in four developing countries - China, Indonesia, Papua New Guinea and Vietnam. The results of our paper suggest that non-linear crowding-out effects are not important features of transfer behaviour in these countries. The transfer derivatives under a variety of assumptions only range between 0 and -0.08. If our results are valid, expansions of public social security to cover the poorest households need not be stymied by offsetting private responses

Improving estimates of inequality and poverty from urban China’s household income and expenditure survey

In urban China the Household Income and Expenditure Survey requires respondents to keep a daily expenditure diary for a full 12-month period. This onerous reporting task makes it difficult to recruit households into the survey, compromising the representative nature of the sample. In this article we use data on the monthly expenditures of households from two urban areas of China to see if data collection short-cuts, such as extrapolating to annual totals from expenditure reports in only some months of the year, would harm the accuracy of annual expenditure, inequality and poverty estimates. Our results show that replacing 12-month diaries with simple extrapolations from either one, two, four or six months would cause a sharp increase in estimates of annual inequality and poverty. This finding also undermines international comparisons of inequality statistics because no country other than China uses such comprehensive 12-month expenditure records. But a corrected form of extrapolation, based on correlations between the same household’s expenditures in different months of the year, gives much smaller errors in estimates of inequality and poverty

Which households are most distant from health centers in rural China? Evidence from a GIS network analysis

In this paper we have two objectives - one empirical; one methodological. Although China’s leaders are beginning to pay attention to health care in rural China, there are still concerns about access to health services. To examine this issue, we use measures of travel distances to health services to examine the nature of coverage in Shaanxi Province, our case study. The mean distance by road to the nearest health center is still more than 6 kilometers. When we use thresholds for access of 5 and 10 kilometers we find that more than 40 (15) percent of the rural population lives outside of these 5 (10) kilometer service areas for health centers. The nature of the access differs by geographical region and demographic composition of the household. The methodological contribution of our paper originates from a key feature of our analysis in which we use Geographic Information System (GIS) network analysis methods to measure traveling distance along the road network. We compare these measures to straight-line distance measures. Road distances (produced by network analysis) produce measures (using means) that are nearly twice as great as straight-line distances. Moreover, the errors in the measures (that is, the difference between road distances and straight-line distances) are not random. Therefore, traditional econometric methods of ameliorating the effects of measurement errors, such as instrument variables regression, will not produce consistent results when used with straight-line distances

IMPROVING ESTIMATES OF INEQUALITY AND POVERTY FROM URBAN CHINA'S HOUSEHOLD INCOME AND EXPENDITURE SURVEY

In urban China the Household Income and Expenditure Survey requires respondents to keep a daily expenditure diary for a full 12-month period. This onerous reporting task makes it difficult to recruit households into the survey, compromising the representative nature of the sample. In this article we use data on the monthly expenditures of households from two urban areas of China to see if data collection short-cuts, such as extrapolating to annual totals from expenditure reports in only some months of the year, would harm the accuracy of annual expenditure, inequality and poverty estimates. Our results show that replacing 12-month diaries with simple extrapolations from either one, two, four or six months would cause a sharp increase in estimates of annual inequality and poverty. This finding also undermines international comparisons of inequality statistics because no country other than China uses such comprehensive 12-month expenditure records. But a corrected form of extrapolation, based on correlations between the same household's expenditures in different months of the year, gives much smaller errors in estimates of inequality and poverty.Consumer/Household Economics,

Missing the marks? Dispersion in corporate bond valuations across mutual funds

We study the dispersion of month-end valuations placed on identical corporate bonds by different mutual funds. Such dispersion is related to bond-specific characteristics associated with liquidity and market volatility. TRACE may have contributed to the general decline in dispersion over our sample period, though other factors most likely played roles. Further tests reveal marking patterns to be consistent with returns smoothing behavior by managers. Funds with ambiguous marking policies and those holding 'hard-to-mark' bonds appear more prone to smooth reported returns. From a regulatory perspective, we see little downside to requiring funds to explicitly state their marking standards. --

Mapping poverty in rural China: how much does the environment matter?

A recently developed small area estimation technique is used to geographically derive detailed estimates of consumption-based poverty and inequality in rural Shaanxi, China. These estimates may be helpful for targeting since there is wide variability in poverty rates within Shaanxi but low levels of inequality within most counties and townships. We also investigate whether including environmental variables in the equation used to predict consumption and poverty improves upon typical approaches that only use household survey and census data. Ignoring environmental variables appears likely to produce targeting errors