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On the relative well-being of the nonmetropolitan poor: an examination of alternate definitions of poverty during the 1990s.

1. Introduction

Understanding the geographic distribution of poverty is important to help target poverty-reduction policies. Throughout the 1980s and 1990s, the proportion of people living in poverty in the United States Poverty in the United States refers to people whose annual family income is less than a "poverty line" set by the U.S. government. Poverty is a condition in which a person or community is deprived of, or lacks the essentials for, a minimum standard of well being and life.  was significantly greater in nonmetropolitan than in metropolitan areas. In the 1980s the average incidence of poverty was 4.4 percentage points larger in nonmetropolitan areas than in metropolitan areas, and in the 1990s the average difference was 2.6 percentage points. (1) Although it is well documented that the incidence of poverty, also called the head count index, has been higher in nonmetropolitan areas, there is very little research that examines whether poverty is deeper or more severe in nonmetropolitan areas.

Zheng zheng (zhēng),
n a Chinese term for an acupuncture diagnosis achieved by thoroughly examining and interviewing a patient.
, Cushing Cush·ing , Harvey Williams 1869-1939.

American surgeon known for his innovations in the field of neurosurgery and for his studies of the pituitary gland.
, and Chow (1995) note that the U.S. Federal Government uses the proportion of poor as virtually the only indicator of poverty. (2) Similarly, much of the academic research on poverty is also focused on the incidence of poverty and does not examine distribution-sensitive measures of poverty. (3) For example, Hanratty and Blank (1992) compare U.S. and Canadian Canadian (kənā`dēən), river, 906 mi (1,458 km) long, rising in NE New Mexico. and flowing E across N Texas and central Oklahoma into the Arkansas River in E Oklahoma.  poverty rates from 1970 to 1986 and provide an explanation for why the Canadian poverty rate improved dramatically relative to the U.S. rate. Sawhill (1988) presents a comprehensive review of poverty measurement in the United States United States, officially United States of America, republic (2005 est. pop. 295,734,000), 3,539,227 sq mi (9,166,598 sq km), North America. The United States is the world's third largest country in population and the fourth largest country in area.  and proposes explanations for why there was so little change in poverty from the mid- mid-
Middle: midbrain. 
1960s to the mid-1980s. Using a consumption-based measure of poverty, rather than the official income-based measure of poverty, Slesnick (1993) counters that there was significant progress made in reducing poverty during this time period.

In all cases, however, when the authors discuss poverty, they are referring to the incidence of poverty and never to any sort of distribution-sensitive measure. Understanding the depth and severity of poverty, in addition to the incidence, may provide information on important differences in the qualitative nature of poverty that would suggest different types of poverty-reduction policies for the different area types.

The purpose of this paper is to examine nonmetropolitan poverty relative to metropolitan and other geographic areas of the United States during the 1990s. This paper extends on the current literature in two ways. First, the analysis considers three different measures of poverty: the head count, poverty-gap, and squared poverty-gap indices. These measures belong to the Foster-Greer-Thorbecke (1984, hereafter In the future.

The term hereafter is always used to indicate a future time—to the exclusion of both the past and present—in legal documents, statutes, and other similar papers.
 referred to as FGT FGT
female genital tract
) family of poverty indices and have been widely used in the international poverty literature. (4) The head count is the standard measure used and provides a measure of the incidence of poverty. The poverty-gap index provides a measure of the depth of poverty, and the squared poverty-gap index is sensitive to the income distribution of the poor and provides a measure of the severity of poverty.

The usefulness of these measures can be illustrated by considering a transfer of money from a rich person to a poor person that is not large enough to push the poor person over the poverty line. This transfer has no effect on the head count index, but the poor person is better off and this welfare improvement is reflected in a reduction of both the poverty-gap and squared poverty-gap indices. As another example, a transfer of income from a poor person to a poorer person will not alter either the head count or the poverty-gap index, but it improves the distribution of income of the poor, and this change is reflected by a reduction of the squared poverty-gap index. (5)

These examples point to an important reason to consider the poverty-gap and squared poverty-gap indices in addition to the commonly reported head count index. A frequently stated goal of many programs is the reduction of poverty, but the policies that are appropriate to attain tiffs goal will vary depending on which poverty measure is considered. If policy makers are focused on the head count index, then the most efficient way to reduce poverty is through assistance to the least poor. If, on the other hand, policy makers are concerned about the overall welfare of the poor and not just on reducing the number of persons living in poverty, then the appropriate measure is one that captures the depth and severity of poverty.

The second way in which this paper extends on the literature is that the statistical tests for differences in poverty are corrected for features of the sample design. (6) Most nationally representative data sets, particularly those from which poverty estimates are formed, are not based on pure random draws from the population; rather they are frequently based on stratified stratified /strat·i·fied/ (strat´i-fid) formed or arranged in layers.

Arranged in the form of layers or strata.
 and multistage mul·ti·stage  
1. Functioning in more than one stage: a multistage design project.

2. Relating to or composed of two or more propulsion units.
 sample designs. As one example, the sample used for the Current Population Survey (CPS (1) (Characters Per Second) The measurement of the speed of a serial printer or the speed of a data transfer between hardware devices or over a communications channel. CPS is equivalent to bytes per second. ) is drawn from a census frame using a stratified, multistage design. Howes Howes can refer to: People
  • Bobby Howes, actor
  • Brian Howes, Canadian musician
  • Greg Howes, soccer player
  • Jimmy Howes, Radio Personality, Program Dir.
 and Lanjouw (1998) present evidence that estimated standard errors for the FGT poverty indices can have large biases when false assumptions are made on the nature of the sample design. In particular they show that if the sample design is multistaged, but standard errors are derived from the incorrect assumption of a simple random sample In statistics, a simple random sample is a group of subjects (a sample) chosen from a larger group (a population). Each subject from the population is chosen randomly and entirely by chance, such that each subject has the same probability of being chosen at any stage during the , then the standard errors will significantly underestimate the true sampling variance The discrepancy between what a party to a lawsuit alleges will be proved in pleadings and what the party actually proves at trial.

In Zoning law, an official permit to use property in a manner that departs from the way in which other property in the same locality
. An example from Jolliffe, Datt DATT Defense Attaché
DATT Department of Aviation Trades Training
DATT Data Access Temporary Table
, and Sharma Sharma is one of the most common Brahmin surnames among Hindus in India, Nepal and other countries. Meaning of the Surname
Sharma is derived from the Sanskrit 'Sharman' which means teacher. According to Sanskrit scholar Dr.
 (in press) shows that in the case of poverty indices for Egypt Egypt (ē`jĭpt), Arab. Misr, biblical Mizraim, officially Arab Republic of Egypt, republic (2005 est. pop. 77,506,000), 386,659 sq mi (1,001,449 sq km), NE Africa and SW Asia. , falling to adjust for the characteristics of the sample design would result in an underestimate of the correct standard errors by 187-212%.

The remaining part of this paper proceeds as follows. Section 2 covers poverty measurement issues, which includes a discussion of the data, poverty line, poverty indices, and the estimates of sampling variance. Section 3 provides a discussion of the results. Examining only the incidence of poverty provides the result that poverty is worse in nonmetropolitan areas during all 10 years of the 1990s. When looking at the depth of poverty, this difference in poverty is only statistically significant in six of the 10 years; and when examining the severity of poverty, the difference is only statistically significant in three of the 10 years (at the 95% confidence level). This section also establishes that there are important nonmetro-metropolitan differences in the distribution of income of the poor and provides further geographic decompositions and some economic explanations for the differences. Section 4 provides a brief conclusion.

2. Poverty Measurement

The 1991-2000 Current Population Survey (CPS) and the U.S. Poverty Thresholds The poverty threshold, or poverty line, is the minimum level of income deemed necessary to achieve an adequate standard of living. In practice, like the definition of poverty, the official or common understanding of the poverty line is significantly higher in developed  

The data used in this paper are from the 1991-2000 March Supplement to the CPS, which is conducted by the by the Bureau of the Census Noun 1. Bureau of the Census - the bureau of the Commerce Department responsible for taking the census; provides demographic information and analyses about the population of the United States
Census Bureau
 for the Bureau of Labor Statistics Bureau of Labor Statistics (BLS)

A research agency of the U.S. Department of Labor; it compiles statistics on hours of work, average hourly earnings, employment and unemployment, consumer prices and many other variables.
. The CPS data are the basis for the official U.S. poverty estimates and provide information on approximately 50,000 households in each year. The March Supplement, also called the Annual Demographic Survey of the CPS, collects information on income and a variety of demographic characteristics. The reference period for income-related questions is the preceding calendar year, and therefore the 1991-2000 CPS data provide poverty estimates for 1990-1999.

The sample is representative of the civilian, noninstitutionalized adj. 1. not committed to an institution; - op people. Opposite of institutionalized nt>.

Adj. 1. noninstitutionalized - not committed to an institution
 population and members of the Armed Forces either living off base or with their families on base. The sample frame is based on housing structures and not individuals, so all individuals who are homeless at the time of the interview are excluded from the sample. Estimates of the number of homeless range from a 1990 Bureau of Census Bureau of Census

A division of the federal government of the United States Bureau of Commerce that is responsible for conducting the national census at least once every 10 years, in which the population of the United States is counted.
 estimate of 250,000 to a 1987 Urban Institute estimate of up to 600,000 service-using homeless individuals. (7) The exclusion of homeless persons An individual who lacks housing, including one whose primary residence during the night is a supervised public or private facility that provides temporary living accommodations; an individual who is a resident in transitional housing; or an individual who has as a primary residence a  from the sample frame is noteworthy for poverty analysis, as this is a group that has a very high incidence of poverty, and it is noteworthy for a geographic analysis of poverty as homeless persons are disproportionately dis·pro·por·tion·ate  
Out of proportion, as in size, shape, or amount.

 located in metropolitan areas. (8)

Because the homeless are disproportionately located in metropolitan areas, their exclusion from the sample biases the estimates in the direction of increasing the estimated gap between metropolitan and nonmetropolitan poverty rotes. Relative to the population of poor persons (estimated at 33.6 million in 1990), the homeless population is small, and this sample-selection bias will not significantly affect the estimated proportion of persons living in poverty. This statement is tempered, however, by noting that the homeless are most likely living in extreme poverty, and their exclusion has a greater impact on the poverty measures that are sensitive to the distribution of income. A primary finding of this paper is that distribution-sensitive measures of poverty reveal that the relative nonmetrometropolitan difference in poverty is smaller than what is indicated by comparing the incidence of nonmetropolitan and metropolitan poverty. If the homeless were included in this analysis, they would reinforce this finding.

The geographical poverty comparisons considered in this paper are primarily between metropolitan and nonmetropolitan areas. (9) Nonmetropolitan is often referred to as rural, but these terms define different geographic areas. (10) The Office of Management and Budget The Office of Management and Budget (OMB), formerly the Bureau of the Budget, is an agency of the federal government that evaluates, formulates, and coordinates management procedures and program objectives within and among departments and agencies of the Executive Branch.  (2002), which issues federal standards for defining statistical areas, states that a metropolitan area is any county that contains a city with a population of at least 50,000, a county with an urbanized area as defined by the Bureau of Census, or a fringe Fringe (optics)

One of the light or dark bands produced by interference or diffraction of light. Distances between fringes are usually very small, because of the short wavelength of light.
 county that is economically tied to a metropolitan area. (11) Nonmetropolitan areas are all areas outside the boundaries of metropolitan areas.

The measure of welfare used in this paper is income as it is defined for federal poverty rates. This definition includes all pretax income pretax income

Reported income before the deduction of income taxes. Pretax income is sometimes considered a better measure of a firm's performance than aftertax income because taxes in one period may be influenced by activities in earlier periods.
, but does not include capital gains or any noncash benefits such as public housing, Medicaid Medicaid, national health insurance program in the United States for low-income persons; established in 1965 with passage of the Social Security Amendments and now run by the Centers for Medicare and Medicaid Services. , or food stamps food stamp
A stamp or coupon, issued by the government to persons with low incomes, that can be redeemed for food at stores.

Noun 1.
. The poverty thresholds used in this paper are the U.S. Federal Government poverty lines, which were developed in 1965 following a cost-of-basic-needs methodology that sets the poverty line at the value of a consumption bundle considered to be adequate for basic consumption needs. Basic needs, in this context, represent a socially determined, normative nor·ma·tive  
Of, relating to, or prescribing a norm or standard: normative grammar.

 minimum for avoiding poverty. For more details on this methodology and other methods of drawing poverty lines, see Ravallion (1998).

The U.S. poverty line set in 1965 was based on the cost of the U.S. Department of Agriculture's (USDA's) economy food plan, a low-cost diet determined to be nutritionally adequate. In addition to the cost of this food plan, the poverty line includes an allowance for nonfood non·food  
Of, relating to, or being something that is not food but is sold in a supermarket, as housewares or stationery.
 expenditures that was twice the value of the cost of the USDA USDA, See United States Department of Agriculture.
 economy food plan. (12) To account for inflation, the poverty lines set in 1965 are adjusted each year using a price index. (13) The latest poverty line used in this study is from 1999, and it is set at $8,667 for an individual under 65 years of age; $11,483 for a two-person family with one child and one adult; and $19,882 for a family with two adults and three children. For a listing of 1999 poverty lines for various family sizes, see Dalaker and Proctor A person appointed to manage the affairs of another or to represent another in a judgment.

In English Law, the name formerly given to practitioners in ecclesiastical and admiralty 
 (2000). (14)

Poverty Measures and Standard Errors

The previous section describes the measure of welfare and poverty lines used to identify who is poor. The next step is to aggregate this information into a scalar scalar, quantity or number possessing only sign and magnitude, e.g., the real numbers (see number), in contrast to vectors and tensors; scalars obey the rules of elementary algebra. Many physical quantities have scalar values, e.g.  measure of poverty. To examine the sensitivity of estimated poverty levels to the choice of a poverty index, I consider three measures that belong to the FGT family. The first is the head count index ([P.sub.0]), which is the percentage of the population living in families with family income less than the poverty line. The second measure is the poverty-gap index (P0, defined by the mean distance below the poverty line (expressed as a proportion of the poverty line), where the mean is formed over the entire population and counts the nonpoor as having zero poverty gap. The third measure is the squared poverty-gap index ([P.sub.2]), defined as the mean of the squared proportionate pro·por·tion·ate  
Being in due proportion; proportional.

tr.v. pro·por·tion·at·ed, pro·por·tion·at·ing, pro·por·tion·ates
To make proportionate.
 poverty gaps.

The FGT class of poverty indices, also referred to as [P.sub.[alpha]] can be represented as

(1) [P.sub.[alpha] = 1/n [summation summation n. the final argument of an attorney at the close of a trial in which he/she attempts to convince the judge and/or jury of the virtues of the client's case. (See: closing argument)  over (i)] I ([y.sub.1] < z)[[(z - [y.sub.1]/z][.sup.[alpha]],

where n is the sample size, i subscript (1) In word processing and scientific notation, a digit or symbol that appears below the line; for example, H2O, the symbol for water. Contrast with superscript.

(2) In programming, a method for referencing data in a table.
 is the family or individual, y is the relevant measure of welfare, z is the poverty line, and I is an indicator function In mathematics, an indicator function or a characteristic function is a function defined on a set that indicates membership of an element in a subset  that takes the value of one if the statement is true and zero otherwise. When [alpha] = 0, the resulting measure is the head count index, or [P.sub.0]. When [alpha] = 1, the FGT index results in the poverty-gap index, or [P.sub.1], and the squared poverty-gap index ([P.sub.2]) results when [alpha] = 2.

In order to answer the question of whether poverty is higher in nonmetropolitan than metropolitan areas, or more generally most any question regarding whether poverty has changed over time or varies over some geographic or demographic characteristic, estimates of the sampling variance for the indices are required. Kakwani (1993) provides two asymptotic estimates for the variance of the FGT poverty indices that are easy to calculate and frequently used. The Kakwani formula for the variance of P0, the head count index, is [P.sub.0](1 - [P.sub.0])/(n - 1), where n is the sample size. The formula for all other variance estimates of the FGT indices is ([P.sub.2[alpha]] - [P.sup.2.sub.[alpha]].)/(n - 1). The primary disadvantage of the Kakwani estimates is that they assume the sample was collected using a simple random draw from the population.

As noted in the introduction, using the Kakwani standard errors when the data were collected from a multistage sample design results in a large underestimate of the true sampling variance. The strategy used in this paper to estimate the design-corrected estimates of sampling variance is to first derive exact estimates for the poverty measures, and then to address the issue of sample design. An advantage of the FGT class of poverty indices in this context is that they are additively decomposable de·com·pose  
v. de·com·posed, de·com·pos·ing, de·com·pos·es
1. To separate into components or basic elements.

2. To cause to rot.

, a characteristic that greatly simplifies deriving exact estimates of the sampling variance of the poverty measures. To illustrate this, consider any income vector y, broken down into M subgroup sub·group  
1. A distinct group within a group; a subdivision of a group.

2. A subordinate group.

3. Mathematics A group that is a subset of a group.

 income vectors, [y.sup.(1)], ..., [y.sup.(m)]. Because P is additively decomposable with population share weights, it can be written as

(2) [MATHEMATICAL EXPRESSION A group of characters or symbols representing a quantity or an operation. See arithmetic expression.  NOT REPRODUCIBLE re·pro·duce  
v. re·pro·duced, re·pro·duc·ing, re·pro·duc·es
1. To produce a counterpart, image, or copy of.

2. Biology To generate (offspring) by sexual or asexual means.
 IN ASCII ASCII or American Standard Code for Information Interchange, a set of codes used to represent letters, numbers, a few symbols, and control characters. Originally designed for teletype operations, it has found wide application in computers. ]

where n is the sample size, [n.sub.j] is the size of each subgroup, and z is again the poverty line. By treating each observation as a subgroup, the estimate of poverty is the weighted mean of the individual-specific measures of poverty and the sampling variance of the poverty measure is the variance of this mean, or


where i subscript is the individual.

The next step is to incorporate the sample design information, which typically requires that the researcher has access to not only unit record data, but also data identifying the characteristics of the sample design. In the case of the CPS data, the sample design information that identifies the strata and primary sampling units (PSUs), has been censored cen·sor  
1. A person authorized to examine books, films, or other material and to remove or suppress what is considered morally, politically, or otherwise objectionable.

 from the public-use files to maintain respondent In Equity practice, the party who answers a bill or other proceeding in equity. The party against whom an appeal or motion, an application for a court order, is instituted and who is required to answer in order to protect his or her interests.  confidentiality. To compensate for the missing design information, the U.S. Bureau of Census (2000, Appendix C) provides detailed notes on how to approximate design-corrected standard errors for a limited set of poverty estimates. An important shortcoming short·com·ing  
A deficiency; a flaw.


a fault or weakness

Noun 1.
 of this method is that parameter (1) Any value passed to a program by the user or by another program in order to customize the program for a particular purpose. A parameter may be anything; for example, a file name, a coordinate, a range of values, a money amount or a code of some kind.  estimates are only provided for the head count index; there are no corrections provided for any other measures of poverty. (15)

In addition to the issue that the Census does not provide sample-design corrections for either the poverty-gap or squared poverty-gap indices, there is the additional problem that the recommended method appears to be significantly less precise for nonmetro-metropolitan comparisons. The proposed correction for all nonmetropolitan statistics provided by the U.S. Bureau of Census (2000, Appendix C) is to multiply mul·ti·ply
1. To increase the amount, number, or degree of.

2. To breed or propagate.
 the design-correction coefficients by 1.5. The implication of this correction is that for all statistics the ratio of the design effects for metropolitan to nonmetropolitan areas is constant. Another factor likely to affect the accuracy of this correction is that it has not been updated in the last 20 years, whereas the design-correction coefficients for all other characteristics are frequently updated. (16)

Given that the Census-recommended method does not provide corrections for the sampling variance of [P.sub.1] and [P.sub.2], and that the adjustment factor for nonmetropolitan areas appears to be a rough approximation approximation /ap·prox·i·ma·tion/ (ah-prok?si-ma´shun)
1. the act or process of bringing into proximity or apposition.

2. a numerical value of limited accuracy.
, I abandoned this method. Instead, I followed an approach based on replicating aspects of the CPS sample design by creating synthetic variables for the strata and clusters that induce in·duce
1. To bring about or stimulate the occurrence of something, such as labor.

2. To initiate or increase the production of an enzyme or other protein at the level of genetic transcription.

 similar design effects. A more detailed description of the approach, and simulation results suggesting that it provides useful approximations, are provided in Jolliffe (2001).

The first step of the synthetic design approach for this analysis of poverty is to sort the data by income. (17) Then each set of four consecutive housing units is assigned as·sign  
tr.v. as·signed, as·sign·ing, as·signs
1. To set apart for a particular purpose; designate: assigned a day for the inspection.

 to a separate cluster. The purpose of the sorting is to induce a high level of intracluster correlation, and the choice of four matches, on average, the actual CPS cluster size. I select the four regions of the United States as synthetic strata to capture the geographic aspect of the CPS stratification stratification (Lat.,=made in layers), layered structure formed by the deposition of sedimentary rocks. Changes between strata are interpreted as the result of fluctuations in the intensity and persistence of the depositional agent, e.g. . The Appendix provides a summary table from Jolliffe (2001) illustrating that the synthetic design approach matches the estimates provided by the Census Bureau Noun 1. Census Bureau - the bureau of the Commerce Department responsible for taking the census; provides demographic information and analyses about the population of the United States
Bureau of the Census
 for the head count index.

With the selection of the synthetic strata and clusters, one can then directly obtain design-corrected estimates of sampling variance based on Equation 3. Following Kish Kish, ancient city, Mesopotamia
Kish, ancient city of Mesopotamia, in the Euphrates valley, 8 mi (12.9 km) E of Babylon and 12 mi (19 km) east of the modern city of Hillah, Iraq.
 (1965) and noting from above that [P.sub.[alpha]] can be considered a sample mean, the estimated sampling variance of the FGT poverty indices from a weighted, stratified, clustered sample is given by


where the h subscripts each of the L strata, i subscripts the cluster or PSU PSU - power supply unit  in each stratum stratum /stra·tum/ (strat´um) (stra´tum) pl. stra´ta   [L.] a layer or lamina.

stratum basa´le
, and j subscripts the ultimate sampling unit (USU USU Usually
USU Utah State University (Logan, UT)
USU Uniformed Services University
USU Ural State University (Ekatherinburg, Russia)
USU Universidade Santa Úrsula
), so [w.sub.hij] denotes the weight for element j in PSU i and stratum h. The number of PSUs in stratum h is denoted by [n.sub.h], and the number of USUs in PSU (h, i) is denoted by [m.sub.hi]. (18)

3. Results

Nonmetro-metropolitan Poverty Comparisons

The purpose of this paper is to examine whether there is more to be learned about the difference between nonmetropolitan and metropolitan poverty than by what is revealed in an analysis of the incidence of poverty ([P.sub.0]). The incidence of poverty is insensitive in·sen·si·tive  
1. Not physically sensitive; numb.

a. Lacking in sensitivity to the feelings or circumstances of others; unfeeling.

 to the income distribution of the poor, whereas [P.sub.1] and [P.sub.2], on the other hand, are distribution sensitive and will reflect differences in well-being. In order to anticipate what the [P.sub.[alpha]] analysis will reveal, it is useful to first examine average income and inequality inequality, in mathematics, statement that a mathematical expression is less than or greater than some other expression; an inequality is not as specific as an equation, but it does contain information about the expressions involved.  of the poor to determine if there are differences in the well-being of the poor by area.

The CPS data indicate that when considering the sample of all persons, average nonmetropolitan income is approximately 25% less than metropolitan income throughout the 1990s. In contrast, Table 1 shows that when restricting the analysis to poor persons, average nonmetropolitan income is greater than average metropolitan income in eight of the 10 years. This difference in area means is not qualitatively large in any year, with the greatest difference at 5% in 1990, nor are any of the differences statistically significant. Nonetheless, this suggests that although overall, nonmetropolitan persons may be worse off, on average the nonmetropolitan poor appear to be as well off as the poor living in metropolitan areas.

Table 1 also reports the Theil measure of inequality for the nonmetropolitan and metropolitan poor. Dasgupta, Sen, and Starrett (1973) show that for a fixed total level of income, any transfer of income that reduces the level of inequality will increase social welfare if the social welfare function is Schur-or quasi-concave. This result illustrates that social welfare can be written as a function of two elements--average income (or the average level of whatever metric is used for welfare) and the distribution of income. The Theil measure of inequality can be expressed as


where Y is average income, i subscript is the individual, and n is the sample size. In general, the Theil index The Theil index[1], derived by econometrician Henri Theil, is a statistic used to measure economic inequality. Mathematics
The formula is

 and the larger family of generalized gen·er·al·ized
1. Involving an entire organ, as when an epileptic seizure involves all parts of the brain.

2. Not specifically adapted to a particular environment or function; not specialized.

 Theil indices have many desirable properties that are described in Foster (1983). (19)

The inequality indices in Table 1 suggest that income of the metropolitan poor is more unequally distributed than for the nonmetropolitan poor throughout the 1990s. The nonmetro-metropolitan inequality difference of the poor ranges from a low of 11% in 1990 and 1992 to a high of 21% in 1996. Estimates of the sampling variance of the indices, based on a bootstrap See boot.

(operating system, compiler) bootstrap - To load and initialise the operating system on a computer. Normally abbreviated to "boot". From the curious expression "to pull oneself up by one's bootstraps", one of the legendary feats of Baron von Munchhausen.
 method that replicates the two-stage nature of the sample design, indicate that the observed inequality differences are statistically significant in all years. (20)

The result that average income for nonmetropolitan and metropolitan poor persons is about the same, whereas the level of inequality for the metropolitan poor is worse, suggests that distribution-sensitive poverty measures will indicate a less stark nonmetro-metropolitan difference in poverty than is indicated by the head count index. Table 2 lists each of the three poverty indices ([P.sub.0], [P.sub.1], and [P.sub.2]) for metropolitan and nonmetropolitan areas. The nonmetropolitan head count index ranges from a high of 0.17 in 1993, representing 9.7 million poor people, to a low of 0.14 in 1999 (7.4 million people). The metropolitan head count index ranges from a high of 0.15 in 1993 (29.5 million people) to a low of 0.11 in 1999, or 24.8 million people living in poverty. The variation in the poverty-gap and squared poverty-gap indices is similar. Across both these measures, for metropolitan and nonmetropolitan areas alike, poverty was at its lowest level in 1999. In terms of the poverty-gap index, the year with the highest level of poverty came in 1993. The worst year, as measured by the squared poverty-gap index, came in 1997 for nonmetropolitan areas and 1993 for metropolitan areas.

One interpretation of the poverty-gap index is that it is equal to the product of the head count index and the income gap, where the income gap is the average shortfall Shortfall

The amount by which the capital required to fulfill a financial obligation exceeds available capital.

Shortfall risk is often combated with an efficient hedging strategy created by a fund, group, institution, or individual.
 of the poor as a fraction of the poverty line. This implies that in 1990 the average shortfall of the poor as a fraction of the poverty line is equal to 40% in nonmetropolitan areas and 44% in metropolitan areas. In 1999, the average shortfall in nonmetropolitan areas is equal to 42% of the poverty line, whereas this shortfall is 46% in metropolitan areas. During all 10 years, the Years, The

the seven decades of Eleanor Pargiter’s life. [Br. Lit.: Benét, 1109]

See : Time
 average shortfall is 3 percentage points greater in metropolitan areas than in nonmetropolitan areas, which indicates that on average the metropolitan poor are worse off than the nonmetropolitan poor.

Table 2 also provides estimates of the design-corrected standard errors, which differentiates this paper from much of the U.S. poverty literature. To examine the magnitude of the adjustments, note that this table provides 60 poverty estimates ([P.sub.0], [P.sub.1], and [P.sub.2] for each year during the 1990s by metropolitan and nonmetropolitan areas). The design effect ranges from a low of 4.3 for the 1995 metropolitan estimate of [P.sub.2] to a high of 5.8 for the 1994 nonmetropolitan estimate of [P.sub.0]. For none of the estimates is the design effect less than 4, which means that the design-corrected standard errors are all more than twice as large as those that would be estimated if one (incorrectly) ignored the complex sample design.

Figure 1 plots the nonmetro-metropolitan percentage differences for the three poverty measures. (21) This figure readily indicates that the largest difference in poverty measurement occurs for the head count index. The incidence of poverty ([P.sub.0]) in nonmetropolitan areas ranges from 16% to 28% worse than in metropolitan areas. This nonmetro-metropolitan difference in poverty is lower when considering the depth of poverty ([P.sub.1] and diminishes even further when considering the severity of poverty ([P.sub.2]). The poverty-gap index for nonmetropolitan areas ranges from 5% to 21% greater than in metropolitan areas, and the squared poverty gap is 1-19% higher in nonmetropolitan than metropolitan areas.


Figure 1 also plots the test statistic statistic,
n a value or number that describes a series of quantitative observations or measures; a value calculated from a sample.


a numerical value calculated from a number of observations in order to summarize them.
 for whether the percentage difference is statistically different from zero. The right-hand side right-hand side nderecha

right-hand side right nrechte Seite f

right-hand side nlato destro 
 of this figure shows that the diminishing di·min·ish  
v. di·min·ished, di·min·ish·ing, di·min·ish·es
a. To make smaller or less or to cause to appear so.

 difference between nonmetropolitan and metropolitan poverty (when considering the depth and severity of poverty) is associated with declining statistical significance of the differences, as one might expect. The incidence of poverty is greater in nonmetropolitan areas, and this difference is statistically significant during all 10 years of the 1990s. If statistical significance is based on a p-value p-value,
n in statistics, the probability that a random variable will be found to have a value equal to or greater than the observed value by chance alone. This value provides an objective basis from which to assess the relative change in the data.
 of less than 0.05 (or the 95% confidence level), then the poverty-gap index is worse in nonmetropolitan areas in six of the 10 years, whereas the squared poverty-gap index is worse in only three of the 10 years. During most of the 1990s, there was no statistically significant difference in the severity of nonmetropolitan and metropolitan poverty.

Examining Tables 1 and 2 together can also provide useful insights into poverty changes during the 1990s. Table 1 indicates that nominal, average income of the poor increased in nonmetropolitan areas by 18% and in metropolitan areas by 21% between 1990 and 1999. During this same time, Table 2 shows that the incidence of poverty fell by 13% in nonmetropolitan and 12% in metropolitan areas. These two pieces of information seem to indicate unambiguous improvement in both metropolitan and nonmetropolitan poverty. This conclusion, however, is misleading because it ignores important changes in the distribution of income. During the 1990s, Table 1 shows that the Theil index of income inequality for the poor increased by 27% in nonmetropolitan areas and by 36% in metropolitan areas. This substantial deterioration de·te·ri·o·ra·tion
The process or condition of becoming worse.
 in the income distribution of the poor worked against the gains in average income and decreases in P0. The net result is that the area-specific measures of the severity of poverty, [P.sub.2], were the same in 1990 as they were in 1999.

Further Geographic Examination of Nonmetropolitan Poverty

Figure 2 furthers the nonmetro-metropolitan poverty comparison by decomposing the metropolitan area into central cities and those metropolitan areas not in central cities (hereafter referred to as suburban). Panel A shows that the nonmetro-suburban poverty comparisons are qualitatively similar to nonmetro-metropolitan comparisons, but the differences are much larger. (22) For all three [P.sub.[alpha]] measures, nonmetropolitan poverty is significantly greater than suburban poverty. The largest difference is in the incidence of poverty, with nonmetropolitan [P.sub.0] being on average 78% greater than the suburban rate. The nonmetro-suburban difference in poverty is lower when considering the depth of poverty ([P.sub.1]) and severity of poverty ([P.sub.2]), but the magnitude of the difference is large. During the 1990s, the nonmetropolitan poverty-gap index is about 69% greater than the suburban rate, and similarly the nonmetropolitan squared poverty-gap index is approximately 60% greater.


The situation is reversed when considering nonmetropolitan poverty relative to poverty in central cities. For all three [P.sub.[alpha]], measures, nonmetropolitan poverty is significantly less than poverty in central cities, and the largest difference is in the severity of poverty. [P.sub.2] is on average 29% lower in nonmetropolitan areas, whereas [P.sub.1] is 26% and P0, 20%. Over all years, the ranking is unchanged, with the largest difference observed for [P.sub.2], followed by [P.sub.1] and the smallest difference for [P.sub.0].

Figures 1 and 2 show that when considering the relative well-being of the nonmetropolitan poor, the incidence of poverty is much larger in nonmetropolitan areas relative to metropolitan areas in general, and suburban areas in particular. An examination of distribution-sensitive poverty indices reduces this difference. In contrast, Figure 2 reveals that the incidence of poverty is lower in nonmetropolitan areas relative to central cities, and an examination of distribution-sensitive measures increases this difference.

To examine nonmetropolitan poverty at a more geographically detailed level, Table 3 provides ordinary least squares (OLS OLS Ordinary Least Squares
OLS Online Library System
OLS Ottawa Linux Symposium
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OLS Online Service
OLS Organizational Leadership and Supervision
OLS On Line Support
OLS Online System
) estimates of the [P.sub.[alpha]] measures for 1999 on three sets of regressors. (23) As a baseline The horizontal line to which the bottoms of lowercase characters (without descenders) are aligned. See typeface.

baseline - released version
, panel A provides the results from regressing [P.sub.[alpha]], on just the nonmetropolitan dummy variable This article is not about "dummy variables" as that term is usually understood in mathematics. See free variables and bound variables.

In regression analysis, a dummy variable
. The point estimates from this panel match the information provided in Table 2 and show that the nonmetro-metropolitan difference is greatest for [P.sub.0] and smallest for [P.sub.2]. Panel B interacts the nonmetropolitan dummy Sham; make-believe; pretended; imitation. Person who serves in place of another, or who serves until the proper person is named or available to take his place (e.g., dummy corporate directors; dummy owners of real estate).  with indicators for the four regions of the United States. The Po estimates from this panel show that the largest nonmetro-metropolitan differences are found in the South and the West, whereas there is no significant difference in the Midwest Midwest or Middle West, region of the United States centered on the western Great Lakes and the upper-middle Mississippi valley. It is a somewhat imprecise term that has been applied to the northern section of the land between the Appalachians . In the Northeast, nonmetropolitan [P.sub.0] is lower than for metropolitan areas. This panel also shows that when considering [P.sub.2], it is still the case that the nonmetropolitan South and West have higher poverty, but now both the nonmetropolitan Midwest and Northeast have lower poverty than their metropolitan areas.

For a final look at the geographic and demographic pattern of poverty, panel C provides fixed-effects estimates controlling for each of the 50 states (plus Washington Washington, town, England
Washington, town (1991 pop. 48,856), Sunderland metropolitan district, NE England. Washington was designated one of the new towns in 1964 to alleviate overpopulation in the Tyneside-Wearside area.
, DC) and conditioning on age, race, and family structure. The estimates indicate that all measures of poverty decline with increases in age for younger persons. As the population ages, [P.sub.0] and [P.sub.1] ultimately start to increase with age. In the case of [P.sub.0], the switching point is at 59 years of age, and for [P.sub.1] it is at 87.5 years. In terms of racial characteristics, black people have much higher rates of poverty across all three measures. Finally, the estimates for family structure reveal that single mothers and single women have higher conditional rates of poverty relative to single men.

The estimates for the nonmetropolitan dummies in panel C show that the qualitative nature of the nonmetro-metropolitan [P.sub.[alpha]] differences found in the univariate univariate adjective Determined, produced, or caused by only one variable  analysis from panel A are robust to the inclusion of the state and demographic controls. The [P.sub.[alpha]], ordering in panel C shows that the difference in conditional poverty measures is greatest for [P.sub.0] and smallest for [P.sub.2]. Quantitatively, the nonmetropolitan point estimates are much larger in panel C than in panel A, indicating that the nonmetro-metropolitan [P.sub.[alpha]] differences are not explained away by the demographic composition of the areas.

Economic Exploration and Policy Implications

The results from above reveal that there am nonmetro-metropolitan differences in the distribution of welfare of the poor. To better understand this result and to draw out some policy implications, it is useful to examine the distribution of area-specific welfare ratios (in other words Adv. 1. in other words - otherwise stated; "in other words, we are broke"
put differently
, the ratio of family income to the poverty line). (24) The advantage of welfare ratios over income is that they provide measures of well-being that control for age and family-size differences across areas. (25) This is because they are a function of the poverty thresholds, which are adjusted to reflect different levels of need for families of various size and age.

Figure 3 provides kernel The nucleus of an operating system. It is the closest part to the machine level and may activate the hardware directly or interface to another software layer that drives the hardware.  density estimates of metropolitan and nonmetropolitan welfare ratios for 1990, 1993, 1996, and 1999. For all years, the nonmetropolitan welfare ratio is more peaked near the poverty line, indicating that a larger proportion of the nonmetropolitan poor subsist sub·sist  
v. sub·sist·ed, sub·sist·ing, sub·sists

a. To exist; be.

b. To remain or continue in existence.

 on greater welfare ratios and are therefore relatively better off. Similarly, the nonmetropolitan welfare ratio lies below the metropolitan distribution on the left-side of the distribution, indicating that a larger proportion of the metropolitan poor live in extreme poverty.


A candidate explanation for this difference in the relative well-being of the nonmetropolitan poor might be based on the conjecture CONJECTURE. Conjectures are ideas or notions founded on probabilities without any demonstration of their truth. Mascardus has defined conjecture: "rationable vestigium latentis veritatis, unde nascitur opinio sapientis;" or a slight degree of credence arising from evidence too weak or too  that a larger proportion of the nonmetropolitan poor are working but employed in low-wage jobs. This hypothesis, however, appears to be rejected by the data. When considering the 1999 sample of civilian adults, the data indicate that the percentage of the metropolitan poor that are not in the labor force (58%) is the same as the nonmetropolitan proportion. Similarly, 22% of both the metropolitan and nonmetropolitan poor work full-time full-time
Employed for or involving a standard number of hours of working time: a full-time administrative assistant.

 schedules, and the remaining 20% (again the same proportion for both metropolitan and nonmetropolitan) work part-time part-time
For or during less than the customary or standard time: a part-time job.

 or are unemployed.

The results are modestly different when considering the 1999 sample of all civilians 15 years and older. In this case, 42% of the nonmetropolitan poor had done some work during 1999, whereas this was true for only 40% of the metropolitan poor. Yet of those persons who worked in the week prior to the survey, the average hours worked during the last seven days by both the metropolitan and nonmetropolitan poor was the same at 34 hours. Similarly, both the metropolitan and nonmetropolitan working poor reported working an average of 35 hours per week and over an average of 34 weeks during 1999.

Although the data do not support the hypothesis that there are significant differences in the proportion of the poor working or the hours they spend working, the data do reveal some important differences in the characteristics of the poor not in the labor force. Of the nonmetropolitan poor who did not work during 1999, 31% reported that they did not work because they were ill or disabled, and 28% reported that they were retired. These proportions for the metropolitan poor are lower, with 26% stating that they were ill or disabled, and 23% that they were retired. In contrast, 22% of the metropolitan poor reported that they did not work because they were going to school, whereas only 16% of the nonmetropolitan poor provided this as a reason.

The contrasting explanations for not working suggest that there might be differences in the nonmetro-metropolitan age composition. Figure 4 shows that the nonmetropolitan age distribution of the poor lies above the metropolitan distribution for higher ages and below for lower ages over the four years considered (1990, 1993, 1996, and 1999). (26) This indicates that the nonmetropolitan poor consist of relatively more persons between the ages of 50 and 90, whereas the metropolitan poor consist of relatively more persons between the ages of 15 and 40. (27) Not surprisingly, sources of income indicate similar nonmetro-metropolitan differences in the age composition of the poor. Twenty-two percent of the nonmetropolitan poor received Social Security payments in 1999, whereas only 16% of the metropolitan poor received Social Security. Twelve percent of the nonmetmpolitan poor received Supplemental Security Income Supplemental Security Income

A Social Security program established to help the blind, disabled, and poor.
 payments, compared with 9% for the metropolitan poor.


4. Conclusion

By using measures of poverty from the Foster-Greer-Thorbecke family of poverty indices, this paper shows that the magnitude and significance of the nonmetro-metropolitan difference in poverty declines when one examines the depth and severity of poverty. Although the incidence of poverty is higher in nonmetropolitan than metropolitan areas throughout the 1990s, the poverty-gap index (depth of poverty) is only statistically significantly worse in nonmetropolitan areas during six of the 10 years, and the squared poverty-gap index (severity of poverty) is worse in only three years (at the 95% confidence level). This result suggests that the nonmetro-metropolitan differences in poverty during the 1990s (as measured by the bead bead

Small object, usually pierced for stringing. It may be made of virtually any material—wood, shell, bone, seed, nut, metal, stone, glass, or plastic—and is worn or affixed to another object for decorative or, in some cultures, magical purposes.
 count index) are not robust to considerations of distribution-sensitive poverty indices.

Further, to test for statistical significance, this paper derives sample design-corrected estimates of sampling variance for any additively decomposable poverty index, such as the [P.sub.[alpha]] indices. Design-corrected standard errors are available for the U.S. head count index in Dalaker and Proctor (2000), but I am aware of no literature on the United States that reports corrected standard errors for any other poverty measure. This paper illustrates the importance of this by noting that standard errors for all 60 reported poverty indices more than doubled in size when corrected.

By examining the ratio of the poverty-gap to the head count index, this paper establishes that the average shortfall of the poor as a fraction of the poverty line is worse in the metropolitan areas during all 10 years of the 1990s. Similarly, the distribution of the welfare ratio (income divided by the poverty line) indicates that the nonmetropolitan poor are relatively better off than the metropolitan poor.

An exploration of economic differences reveals that approximately the same proportion of the metropolitan and nonmetropolitan poor are active in the labor force and appear to work about the same number of hours per year. A comparison of the poor who are not in the labor force indicates that nonmetropolitan persons not in the labor force are more likely to be disabled and retired, whereas the nonworking, metropolitan poor are more likely to be going to school. This distinction is further supported by the data indicating that nonmetropolitan areas consist of relatively more older poor people, whereas proportionately pro·por·tion·ate  
Being in due proportion; proportional.

tr.v. pro·por·tion·at·ed, pro·por·tion·at·ing, pro·por·tion·ates
To make proportionate.
 more younger poor people reside in metropolitan areas. These differences are consistent with the supposition that nonmetropolitan areas are relatively cheaper and therefore more attractive to poor persons on fixed incomes. Attracting more jobs to these areas or providing job-training programs would presumably pre·sum·a·ble  
That can be presumed or taken for granted; reasonable as a supposition: presumable causes of the disaster.
 help many, but they will be of relatively less value to the retired and disabled.

The results on the incidence of poverty support the notion that poverty-reduction policies should include components that target nonmetropolitan areas. The distribution-sensitive poverty measures suggest that different policies may be appropriate for each area. One type of poverty-reduction strategy would be to focus on helping the young and poor get the necessary skills to enhance their opportunities in the labor market labor market A place where labor is exchanged for wages; an LM is defined by geography, education and technical expertise, occupation, licensure or certification requirements, and job experience . Another type of antipoverty an·ti·pov·er·ty  
Created or intended to alleviate poverty: antipoverty programs. 
 program would be to simply provide income assistance to help ease the burden of poverty for those who are retired or unable to work. Since many of these people live on fixed incomes, they are not the extreme poor, and a modest supplement to their income would likely increase their income to a level greater than the poverty line. The poor in both metropolitan and nonmetropolitan areas share many similarities and need both types of programs. Policies aimed at metropolitan areas, however, would be of more value if they had relatively more focus on mitigating mit·i·gate  
v. mit·i·gat·ed, mit·i·gat·ing, mit·i·gates
To moderate (a quality or condition) in force or intensity; alleviate. See Synonyms at relieve.

To become milder.
 extreme poverty, whereas nonmetropolitan areas would benefit relatively more from a somewhat greater focus on supplemental income assistance for the elderly and disabled.
Table 1. Income and Inequality of the Poor, Nonmetro-metropolitan

           Average Income Level of Poor Persons

Year    Nonmetro    Metro     Difference    Percent

1990     7229       6896         333           5%
         (153)       (97)       (181)
1991     7243       6995         248           4%
         (150)       (91)       (175)
1992     7316       7113         203           3%
         (153)       (92)       (178)
1993     7608       7428         181           2%
         (145)      (105)       (179)
1994     7630       7617          13           0%
         (163)      (106)       (194)
1995     8231       8031         200           2%
         (212)      (117)       (242)
1996     8104       8121         (17)          0%
         (202)      (123)       (237)
1997     7952       8100         149          -2%
         (187)      (130)       (228)
1998     8395       8104         291           4%
         (224)      (123)       (255)
1999     8517       8372         145           2%
         (237)      (145)       (278)

             Theil Index of Inequality for the Poor

Year    Nonmetro    Metro    Difference    t-statistic (a)

1990     0.221      0.247      -0.026           2.00

1991     0.218      0.252      -0.034           2.61

1992     0.233      0.260      -0.028           1.96

1993     0.226      0.278      -0.051           3.85

1994     0.237      0.271      -0.034           2.20

1995     0.232      0.278      -0.045           2.71

1996     0.226      0.285      -0.059           3.58

1997     0.272      0.314      -0.042           2.17

1998     0.270      0.332      -0.063           3.08

1999     0.281      0.336      -0.055           2.61

Income is in nominal U.S. dollars. The column headed Percent lists the
difference between nonmetropolitan and metropolitan average income,
using metropolitan as the base. Standard errors for income measures, in
parentheses, are corrected for sample design effects following the
synthetic-design approach described in Jolliffe (2001). Standard errors
for the inequality indices are bootstrap estimates based on 1000
bootstrap samples and a resampling method that replicates the two-stage
nature of the sample design. For details, see Jolliffe and
Krushelnytskyy (1999).

(a) t-statistic is for the null hypothesis that the
nonmetro-metropolitan difference in inequality index is equal to zero.

Table 2. Incidence, Depth, and Severity of Poverty,
Nonmetro-metropolitan Comparisons

        Headcount, [P.sub.0]    Poverty-gap, [P.sub.1]

Year    Nonmetro    Metro       Nonmetro    Metro

1990     0.163       0.127       0.066       0.056
        (0.0042)    (0.0022)    (0.0021)    (0.0012)
1991     0.160       0.137       0.067       0.061
        (0.0042)    (0.0023)    (0.0022)    (0.0013)
1992     0.167       0.139       0.071       0.063
        (0.0042)    (0.0023)    (0.0022)    (0.0013)
1993     0.171       0.146       0.072       0.067
        (0.0043)    (0.0025)    (0.0022)    (0.0014)
1994     0.159       0.141       0.068       0.065
        (0.0043)    (0.0025)    (0.0023)    (0.0014)
1995     0.156       0.134       0.064       0.060
        (0.0049)    (0.0024)    (0.0026)    (0.0013)
1996     0.159       0.132       0.067       0.059
        (0.0048)    (0.0023)    (0.0025)    (0.0013)
1997     0.158       0.126       0.070       0.058
        (0.0048)    (0.0023)    (0.0027)    (0.0013)
1998     0.143       0.123       0.061       0.057
        (0.0046)    (0.0023)    (0.0024)    (0.0013)
1999     0.142       0.112       0.060       0.052
        (0.0046)    (0.0022)    (0.0025)    (0.0012)

        Squared Poverty-gap,

Year    Nonmetro    Metro

1990     0.039       0.035
        (0.0015)    (0.0009)
1991     0.041       0.039
        (0.0016)    (0.0010)
1992     0.044       0.040
        (0.0017)    (0.0010)
1993     0.044       0.043
        (0.0017)    (0.0011)
1994     0.043       0.042
        (0.0017)    (0.0011)
1995     0.039       0.039
        (0.0020)    (0.0010)
1996     0.041       0.038
        (0.0019)    (0.0010)
1997     0.046       0.038
        (0.0021)    (0.0010)
1998     0.039       0.039
        (0.0019)    (0.0010)
1999     0.039       0.035
        (0.0020)    (0.0010)

Poverty indices are the Foster-Greer-Thorbecke [P.sub.[alpha]] indices.
The incidence of poverty is measured by [P.sub.0], the depth by
[P.sub.1], and the severity by [P.sub.2]. Standard errors, in
parentheses, are estimated following Equation 4 using the program
described in Jolliffe and Semykina (1999).

Table 3. Regression Analysis of Poverty in 1999

                                     [P.sub.0]: Incidence

                                      Estimate      Error

Panel A: baseline
  Nonmetro Dummy                      0.030 ***    (0.0050)
Panel B: regional analysis
  Nonmetro Northeast                 -0.018 *      (0.0096)
  Nonmetro Midwest                    0.002        (0.0085)
  Nonmetro South                      0.058 ***    (0.0080)
  Nonmetro West                       0.042 ***    (0.0107)
Panel C: demographic analysis (a)
  Nonmetro Dummy                      0.052 **     (0.0050)
  Age in years/10                    -0.039 ***    (0.0017)
  Age squared/1000                    0.033 ***    (0.0020)
  Race: black                         0.081 ***    (0.0070)
  Husband and wife
    family                           -0.118 ***    (0.0053)
  Single-mother family                0.093 ***    (0.0082)
  Single-father family               -0.067 ***    (0.0094)
  Female individual                   0.057 ***    (0.0067)

                                        [P.sub.1]: Depth

                                      Estimate      Error

Panel A: baseline
  Nonmetro Dummy                      0.009 ***    (0.0027)
Panel B: regional analysis
  Nonmetro Northeast                 -0.014 ***    (0.0048)
  Nonmetro Midwest                   -0.004        (0.0042)
  Nonmetro South                      0.021 ***    (0.0045)
  Nonmetro West                       0.015 ***    (0.0058)
Panel C: demographic analysis (a)
  Nonmetro Dummy                      0.019 ***    (0.0027)
  Age in years/10                    -0.014 ***    (0.0009)
  Age squared/1000                    0.008 ***    (0.0011)
  Race: black                         0.036 ***    (0.0040)
  Husband and wife
    family                           -0.069 ***    (0.0033)
  Single-mother family                0.040 ***    (0.0051)
  Single-father family               -0.045 ***    (0.0052)
  Female individual                   0.021 ***    (0.0043)

                                      [P.sub.2]: Severity

                                      Estimate      Error

Panel A: baseline
  Nonmetro Dummy                      0.004 *      (0.0022)
Panel B: regional analysis
  Nonmetro Northeast                 -0.011 ***    (0.0038)
  Nonmetro Midwest                   -0.005 *      (0.0032)
  Nonmetro South                      0.012 ***    (0.0037)
  Nonmetro West                       0.009 *      (0.0050)
Panel C: demographic analysis (a)
  Nonmetro Dummy                      0.011 ***    (0.0023)
  Age in years/10                    -0.008 ***    (0.0008)
  Age squared/1000                    0.003 ***    (0.0009)
  Race: black                         0.022 ***    (0.0033)
  Husband and wife
    family                           -0.055 ***    (0.0029)
  Single-mother family                0.018 ***    (0.0044)
  Single-father family               -0.039 ***    (0.0044)
  Female individual                   0.015 ***    (0.0039)

Estimates are weighted ordinary least squares (OLS) and standard errors
are corrected for sample design effects as described in the paper.
Sample size is 133,710 for panels A and B and 133,380 for panel C.
Across all three panels the [R.sup.2] is less than 0.11. The intercept
is suppressed from the output for brevity.

(a) Estimates control for state fixed effects.

* P < 0.1.

** P < 0.05.

*** P < 0.01.


Confidence Intervals from Synthetic-Design and Census-Recommended
Corrections, 1999 CPS Poverty Indices

                                   Estimated 90% Confidence Intervals

   Poverty              Percent    Reported     Implied        a,b
Characteristic           Poor      Table A     by Levels    Percentage

Persons, total           11.8        0.3         0.33          0.33
Persons, in families     10.2        0.3         0.34          0.34
Race, white persons       9.8        0.3         0.34          0.33
Race, black persons      23.6        1.2         1.20          1.20
Age, under 18 years      16.9        0.7         0.65          0.65
Age, 18-64 years         10.0        0.3         0.39          0.39
Age, 65 years+            9.7        0.5         0.53          0.53
Families, total           9.3        0.3         0.33          0.28

                           Estimated 90% Confidence Intervals

   Poverty               a,b     Match a,b     Synthetic    Random
Characteristic          Ratio    Categories     Design      Sample

Persons, total            *         yes          0.33        0.16
Persons, in families      *          no          0.36        0.17
Race, white persons       *         yes          0.31        0.16
Race, black persons       *         yes          1.24        0.66
Age, under 18 years     0.66       yes/no        0.64        0.37
Age, 18-64 years          *          no          0.30        0.20
Age, 65 years+          0.53        yes          0.53        0.43
Families, total         0.34        yes          0.32        0.29

Edited table from Jolliffe (2001). Confidence intervals are in
percentage points, and asterisk denotes an undefined number. The first
four columns of confidence intervals are derived from Dalaker and
Proctor (2000). The bold estimate marks whether the U.S. Bureau of
Census considers the estimate a percentage or ratio. The next column
lists whether there is a direct match in characteristics between the
poverty estimates and those characteristics assigned a,b coefficients.
The estimates from the synthetic cluster approached are listed next,
followed by the confidence intervals from assuming that the data are
from a weighted, simple random sample.

I thank John Cromartie Cromartie is a fictional character portrayed by Owain Yeoman and Garret Dillahunt in the upcoming television series, . He is a Terminator sent back from the future to kill John Connor. , Linda A set of parallel processing functions added to languages, such as C and C++, that allows data to be created and transferred between processes. It was developed by Yale professor David Gelernter, when he was a 23-year old graduate student.  Ghelfi, Robert Gibbs Robert Gibb RSA (28 October 1845 - 11 February 1932) was a Scottish painter who was Keeper of the National Gallery of Scotland from 1895 to 1907 and was Painter and Limner to the King from 1908 until his death. . Craig Craig   , Edward Gordon 1872-1966.

British theatrical producer, director, and designer whose innovative productions and simplified stage designs influenced modern theater.
 Gundersen Gundersen is a surname. It may refer to:

  • Bjørn Gundersen (1924–), Norwegian high jumper
  • Einar 'Jeja' Gundersen (1896–1962), Norwegian footballer
  • Erik Gundersen (1959–), Danish speedway rider
, George Hammond George S. Hammond is a fictional character in the Stargate SG-1 television program, played by Don S. Davis. Biography
Major General Hammond was the head of the USAF's Stargate Command.
, Signe-Mary McKernan, Tim Parker, Caroline Ratcliffe, Laura Tiehen, Leslie Whitener whit·en  
tr. & intr.v. whit·ened, whit·en·ing, whit·ens
To make or become white or whiter, especially by bleaching.

, Josh JOSH Joshua
JOSH Job Scheduling Hierarchically
 Winicki, conference participants at the Southern Regional Science Association, and seminar participants at the Urban Institute and at the Society for Government Economists for comments. The views and opinions expressed in this paper do not necessarily reflect the views of the Economic Research Service of the U.S. Department of Agriculture.

(1) Nord (1997) end Jolliffe (2002) show that the incidence of poverty is greater in nonmetropolitan areas.

(2) An exception to this is the Census Bureau P-60 series (for example, Dalaker and Proctor 2000) report of the number of persons with income less than various ratios of the poverty line.

(3) There are some noteworthy exceptions. Cushing and Zheng (2000) use distribution-sensitive measures to compare regional poverty differences using 1990 Census data. Zheng, Cushing. and Chow (1995) consider several distribution-sensitive indices and test for change in poverty from 1975 to 1990; and Bishop, Formby, and Zheng (1999) examine regional differences in Sen's (1976) distribution-sensitive index from 1961 to 1996. An important methodological difference between these last two articles and the results reported in this paper is that the statistical tests considered in this paper correct for the characteristics of the sample design.

(4) The following all use these three measures: Jolliffe, Datt, and Sharma (in press) for Egypt, Dart dart

see blow dart.

dart gun
see blow dart.
 and Ravallion (1992) cover Brazil and India, Howes and Lanjouw (1998) use examples from Pakistan and Ghana, Kakwani (1993) examines Cote d'Ivoire, and Ravallion and Bidani (1994) examine Indonesia.

(5) Unlike the Sen (1976) or Kakwani (1980) distribution-sensitive measures of poverty, the squared poverty-gap index also satisfies the "subgroup consistency" property, which means that if poverty increases in any subgroup and it does not decrease elsewhere, then aggregate poverty must also increase (Foster and Shorrocks 1991).

(6) Zheng (2001) provides design-corrected estimates of sampling variance for poverty estimates based on relative poverty lines (i.e., the poverty line is relative to the distribution of income, such as one half the median income level). The advantage of the estimates provided in this paper is that they are based on a fixed (or absolute) poverty line, which is how poverty is measured in the United States. Another advantage is that Jolliffe and Semykina (1999) provide a Stata Stata (Statistics/Data Analysis) is a statistical program created in 1985 by Statacorp that is used by many businesses and academic institutions around the world. Most of its users work in research, especially in the fields of economics, sociology, political science, and  program that estimates the standard errors presented in this paper.

(7) For a discussion of measures of homelessness and potential explanations for the rising incidence, see Quigley, Raphael, and Smolensky (2001) and Honig and Filer (1993).

(8) For a discussion of income levels and geographical distribution the natural arrangements of animals and plants in particular regions or districts.
See under Distribution.

See also: Distribution Geographic
 of homelessness, see chapter 5 and 13 of Urban Institute (1999).

(9) The analysis does also consider central cities and suburbs as a subset A group of commands or functions that do not include all the capabilities of the original specification. Software or hardware components designed for the subset will also work with the original.  of metropolitan areas, as well as an examination of nonmetropolitan poverty controlling for state fixed effects.

(10) Cromartie (2000) shows that 21% of the population live in nonmetropolitan areas, 25% in rural areas, and 64% of persons living in nonmetropolitan areas also live in rural areas.

(11) For details of the definition, see Office of Management and Budget (2000).

(12) For details on the first poverty lines, see Orshansky (1965). For a history of poverty lines prior to Orshansky, see Fisher (1997). For a critical discussion of the poverty line, see Ruggles (1990).

(13) Prior to 1969, the index used was the changing cost of the USDA economy food plan, and afterward af·ter·ward   also af·ter·wards
At a later time; subsequently.

Adv. 1. afterward - happening at a time subsequent to a reference time; "he apologized subsequently"; "he's going to the store but he'll be back here
, the Consumer Price Index (CPI (1) (Characters Per Inch) The measurement of the density of characters per inch on tape or paper. A printer's CPI button switches character pitch.

(2) (Counts Per I
) for all goods and services In economics, economic output is divided into physical goods and intangible services. Consumption of goods and services is assumed to produce utility (unless the "good" is a "bad"). It is often used when referring to a Goods and Services Tax.  has been used.

(14) The analysis in this paper is based on the full CPS sample, which includes all persons living alone and in families. A family is defined as a group of two or more persons residing together and related by birth, marriage, or adoption. Families also include any related subfamily subfamily /sub·fam·i·ly/ (sub´fam-i-le) a taxonomic division between a family and a tribe.

A taxonomic category ranking between a family and a genus.
 members, where a subfamily is defined as a married couple with or without children, or a parent with single children under 18 years of age.

(15) Another shortcoming of the Census-recommended method is that corrections are only provided for a limited set of characteristics. For example, U.S. Bureau of Census (2000, Appendix C) provides parameter estimates to adjust the sampling variance for the head count index by several age categories. If the analysis is focused on individuals 15-24 years of age, the analyst is provided with parameter estimates. If the relevant subsample sub·sam·ple  
A sample drawn from a larger sample.

tr.v. sub·sam·pled, sub·sam·pling, sub·sam·ples
To take a subsample from (a larger sample).
 is, say, working-age adults, the Census does not provide the necessary parameters to estimate standard errors.

(16) Personal communication with the Census appears to support this assertion that the nonmetropolitan adjustment is less precise: "The factor of 1.5 has been used for nonmetropolitan areas as a simple approximation. While the best factor likely varies from characteristic to characteristic, we use 1.5 for all characteristics, rather than publishing a different factor for each estimate. Years ago, someone looked at the data for metro/nonmetropolitan areas and decided that 1.5 would be a good, and somewhat conservative, estimate for most characteristics."

(17) The methodology requires sorting the data on the variable most relevant to the analysis.

(18) The poverty and sampling variance estimates are documented in more detail in Jolliffe and Semykina (1999), which also provides a program to estimate Equation 4 in the Stata software.

(19) In particular, Foster (1983) shows that an inequality index satisfies the axioms This is a list of axioms as that term is understood in mathematics, by Wikipedia page. In epistemology, the word axiom is understood differently; see axiom and self-evidence. Individual axioms are almost always part of a larger axiomatic system.  of symmetry symmetry, generally speaking, a balance or correspondence between various parts of an object; the term symmetry is used both in the arts and in the sciences. , replication In database management, the ability to keep distributed databases synchronized by routinely copying the entire database or subsets of the database to other servers in the network.

There are various replication methods.
 invariance in·var·i·ant  
1. Not varying; constant.

2. Mathematics Unaffected by a designated operation, as a transformation of coordinates.

An invariant quantity, function, configuration, or system.
, income scale independence, decomposability, and the principle of transfers only if it is a positive multiple of the Theil index.

(20) The bootstrap estimates are based on 1,000 replications. For methodology details and the program used, see Jolliffe and Krushelnytskyy (1999). Lorenz curves The Lorenz curve is a graphical representation of the cumulative distribution function of a probability distribution; it is a graph showing the proportion of the distribution assumed by the bottom y% of the values.  are art alternative way to examine inequality, and Zheng (2002) derives asymptotic covariance Covariance

A measure of the degree to which returns on two risky assets move in tandem. A positive covariance means that asset returns move together. A negative covariance means returns vary inversely.
 structure for generalized Lorenz curves when the sample is based on a complex design.

(21) The relative difference in poverty uses the metropolitan poverty level as the base and can be expressed as [([P.sub.[alpha]nonmetropolitan] - [P.sub.[alpha]metropolitan])/[P.sub.[alpha]metropolitan]].

(22) All differences listed in Figure 2 are statistically significant with p-values less than 0.01.

(23) I use OLS, rather than a censored regression model Censored regression models commonly arise in econometrics in cases where the variable of interest is only observable under certain conditions. A common example is labor supply. , because the zero values for each of the [P.sub.[alpha]] indices are the actual values and do not represent censored values. The estimates are weighted and design corrected.

(24) Blackorby and Donaldson (1987), using this terminology, provide an analysis of welfare ratios as an index of well-being in cost-benefit analysis cost-benefit analysis

In governmental planning and budgeting, the attempt to measure the social benefits of a proposed project in monetary terms and compare them with its costs.

(25) For example, in 1999 the average age of a metropolitan poor person was 28 years compared with 32 years for the nonmetropolitan poor. In terms of family size, 16% of the metropolitan poor lived in two-person families compared with 20% for the nonmetropolitan poor.

(26) The result that there are systematic differences in the metro-nonmetropolitan age distribution of the poor does not mean that the metro-nonmetropolitan poverty difference is the result of this age difference. In fact, the poverty regressions in panel C of Table 3 indicate just the opposite. If the age distribution in nonmetropolitan areas were the same as in metropolitan areas, then the metro-nonmetropolitan poverty difference would be even larger. The relevance of the area difference in age distribution is that it indicates a potential case for slight differences in how poverty alleviation policies are designed for each area.

(27) This difference in the age distribution is also partially evident in family structure characteristics. Thirty-nine percent of the metropolitan poor live in single-mother families, whereas 32% of the nonmetropolitan poor are in single-mother families.


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Zheng, Bubong, Brian Cushing Brian Cushing is a strongside linebacker for the University of Southern California Trojans football team. College career
Cushing shares the #10 with starting quarterback John David Booty.
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Dean Jolliffe, Economic Research Service, U.S. Department of Agriculture, Room S-2059, 1800 M Street NW, Washington, DC, 20036-5831; E-mail:

Received June 2002; accepted December 2002.
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