Hofsra Universiy From he SelecedWorks of Lonnie K. Sevans Spring March, 2008 The Relaionship Beween Povery and Economic Growh Revisied Lonnie K. Sevans, Hofsra Universiy David N. Sessions, Hofsra Universiy Available a: hp://works.bepress.com/lonnieksevans/4/
Published in he Journal of Income Disribuion, 17(1), March 2008, pp. 5-20. The Relaionship Beween Povery and Economic Growh Revisied Absrac I has been shown in prior research ha increased economic growh reduces povery. Auhors have also found ha he effec of growh in GDP on povery growh has eiher diminished or remained unchanged over ime and he 1980s economic expansion in he U.S. had no affec on povery. Using a formal error-correcion model, we find ha increases in economic growh are significanly relaed o reducions in he povery rae for all families. Specifically, GDP growh was found o have a more pronounced effec on povery during he expansionary periods of he 1960s, 1970s, 1980s, 1990s, and 2000s. Oher findings include idenificaion of deerminans of he dynamic behavior of povery raes boh in he year-o-year periods and over he long-run. JEL Codes: C32, I32, O40 Keywords: povery, economic growh, income inequaliy, error-correcion, coinegraion This research was suppored by a Summer Research Gran from he Zarb School of Business.
2 Lonnie K. Sevans Associae Professor Zarb School of Business Deparmen of BCIS/QM 127 Hofsra Universiy Hempsead, NY 11549-1270 516 463-5375 acslks@hofsra.edu hp://www.i2.i-2000.com/~acslks/lks.hml David N. Sessions Associae Professor Zarb School of Business Deparmen of BCIS/QM 127 Hofsra Universiy Hempsead, NY 11549-1270 516 463-5719 david@sessionsdp.com
3 Inroducion According o he U.S. Census Bureau saisics, povery raes have declined precipiously since 1959. 1 The official povery rae has decreased from 22.4 percen of families in povery in 1959 o 12.7 percen in 2004. Prior research in his area of sudy has concluded ha his large decline in povery raes may in fac be due o increased economic growh (Plonick and Skidmore (1975), Aaron (1967), Perl and Solnick (1971), and Adams (2002). Of course, his progression of povery raes may have also resuled from oher facors, such as increases in ransfer paymens, more efficien labor markes, or from auspicious developmens in he areas of educaion or discriminaion (Thornon, e. al., (1978)). From a policy perspecive, as long as here is a srong negaive correlaion beween economic growh and povery ha is expeced o las ino he fuure, hen here may be less need for governmen programs ha are inended o specifically reduce povery. Consequenly, i is imporan o know wheher changes in he relaionship beween GDP and povery will endure for he presen and ino he fuure. Many of he early invesigaions ino he rickle-down model of economic growh in he U.S. have confirmed ha economic growh alleviaes povery by increasing employmen and/or he real wage (Anderson (1964), Thornon, e al. (1978), and Hirsh (1980)). Since pas empirical sudies have shown ha growh and income inequaliy are no relaed, susained economic growh should have a large or more han proporionae effec on he povery rae by raising everyone s income including he poor. 2 One of he 1 2 hp://www.census.gov/hhes/income/hisinc/hispovb.hml The empirical sudies will be presened in he nex secion.
4 discoveries of curren research on his heme is ha he economic expansion of he 1980s did no reduce povery significanly. Boh Blank (1993) and Formby, e al. (2001) found ha povery in he 1960s was more responsive o economic expansion han i was in he 1980s. An explanaion given was he sluggish growh of U.S. real wages in he 1980s real wages of low-income workers rose by only one half of one percen during he 1980s expansion (Formby, e. al. (2001)). However, real wages can remain sagnan while real incomes increase due o improved employmen opporuniies. Real wages increased in he 1990s expansion by only one enh of one percen, ye povery declined by 3.7 percen. 3 In his paper, we will invesigae he dynamic relaionship beween economic growh and povery in he conex of a formal, error-correcion model. While previous auhors have esimaed regressions using differenced variables, hese model specificaions have no allowed for he prospec of an error-correcing or long-run relaionship among povery and is ime series deerminans. Moreover, failure o consider his may have biased he resuls of previous sudies, since he error-correcing erm was omied. We will also include a measure of income inequaliy as a deerminan of povery. In addiion o analyzing he expansionary periods of he 1960s and 1980s, as prior sudies have done, we will also include he 1970s, 1990s and 2000s. The ime period uilized for his analysis is from 1959 o 2004 and he frequency is annual. 3 hp://www.haverselec.com
5 Lieraure Review and Pas Model Specificaions Povery, Economic Growh and Inequaliy Do he poor benefi from economic growh? On one hand, i is argued ha he poenial effec of economic growh on povery raes is offse eiher enirely or in par by an increase in income inequaliy. Alernaively, economic growh may reduce povery by raising he incomes of everyone in sociey, including he poor (Dollar and Kraay (2001)). The former asserion finds is roos in he Kuznes hypohesis (1955), posiing ha growh and inequaliy are relaed hrough an invered U shaped funcion. The implicaion here is ha if economic growh leads o increased inequaliy, hen he growh effec on povery would be enuous a bes. The problem wih he Kuznes hypohesis (1955) is ha he relaionship beween economic growh and inequaliy was derived from cross secional daa, e.g., using counries a differen poins of developmen a he same poin in ime, whereby wha was really needed o es he hypohesis would be ime series daa (Adams (2002)). There are a number of empirical sudies ha have rejeced he Kuznes hypohesis (1955) (Ravallion (1995), Deininger and Squire (1996, 1998), Schulz (1998), and Bruno, e. al. (1998). There appears o be a consensus in he lieraure ha economic growh does no have much of an impac on inequaliy, because income disribuions do no change appreciably over ime. Deininger and Squire (1996) found ha gross domesic produc per capia increased by 26 percen in he developing world beween 1985 and 1995, while Gini coefficiens changed by only 0.28 percenage poins over he same period. Our invesigaion ino his relaionship uilizing more curren economeric echniques yielded
6 comparable resuls, e.g., i was found ha over he period 1959 o 2004, inequaliy, as measured by he Gini coefficien, was no coinegraed wih Gross Domesic Produc. 4 There is some evidence ha economic growh has reduced povery in developing counries. Squire (1993) found ha a en percen increase in he growh rae reduced povery across a sample of counries by 24 percenage poins. In a similar sudy by Bruno, e. al. (1998), a en percen increase in growh was associaed wih a 21.2 percen decrease in he povery rae for a sample of 20 counries over he period 1984-1993. There is also evidence ha changes in inequaliy can affec changes in povery, ceeris paribus. In he same aforemenioned sudy by Bruno, e. al. (1998), he auhors realized a posiive and saisically significan elasiciy esimae of 3.86 on he inequaliy variable (Gini coefficien), leading hem o conclude ha even small changes in he overall disribuion of inequaliy can lead o sizeable changes in he incidence of povery (Bruno, e. al. (1978). However, rising income inequaliy could also be associaed wih declines in povery raes. This could resul from a burs in echnological change ha would creae forunes for enrepreneurs/managers and conemporaneously improve he wages of hose a he boom of income scale. This occurred during he Indusrial Revoluion in Briain and he informaion echnology boom in he Unied Saes. Moreover, higher skill levels required by new echnology creae a demand for advanced educaion and raining. An increase in he quaniy and qualiy of educaion would generae a wider dispariy beween skilled and unskilled workers--conribuing o greaer income inequaliy. A beer educaed labor force is also associaed wih declines in 4 For reasons of breviy, hese resuls were no included in his sudy bu will be made available upon reques from he auhors.
7 povery. The povery rae in 2004 among college educaed persons is 4.3 percen compared o 11.9 percen for hose who have high school educaion. 5 Empirical Specificaions Using ime series daa, previous auhors who conduced research on his opic uilized regression analysis wih variables ha were eiher firs differenced or percen differenced, e.g., in firs differenced form, P = + GDP + U + TR + FEM + D GDP + (1) β0 β1 β2 β3 β4 β5 ε, where, P GDP U TR FEM D - change in family povery rae - change in gross domesic produc, - change in he male unemploymen rae, - change in ransfer paymens, - change in number of female headed households, - dummy variable, D GDP - ineracion erm. Muliple ineracion erms may also be presen. They are included in hese ypes of models in order o ascerain wheher he impac of growh on povery is dissimilar for differen years--he dummy variable would represen differen ime periods. Thornon, e al. (1978) found his ineracion erm o be negaive and saisically significan in he pos 1963 period relaive o he 1947-1963 period concluding, (in heir words), ha rickle-down has peered-ou. A leas hree of he above explanaory variables have been used in model specificaions in pas research. 6 5 6 hp://pubdb3.census.gov/macro/032005/pov/new29_100_01.hm Thornon, e al. (1978) omis he female-headed households variable, while Formby, e al. (2001) includes i along wih wo ineracion erms for he expansionary periods 1962 1972 and 1983-1989.
8 The specificaion of equaion (1) is raher ypical. Economic growh is calculaed by he change or percenage change in GDP, while he oher variables serve as conrols. Thornon, e al. (1978) and Blank (1993) poin-ou ha female-headed households demonsrae above average povery raes, and increases in he male unemploymen rae are undoubedly associaed wih increases in povery. The male unemploymen rae is used because i is more sable han he overall rae (Formby, e. al. (2001)). However, as argued by Blank (2003), here are conflicing resuls concerning he effec of ransfer paymens on povery. According o Wallace and Blank (1999), ransfer paymens canno only direcly reduce povery, bu can cause hose in povery o find employmen as here are reducions in welfare case loads. Alernaively, some auhors such as Recor and Lauder (1995) believe in he welfare dependency hypohesis; ha is, ransfer programs can increase povery by diminishing he incenives o look for and mainain gainful employmen. The impac ha ransfers have on povery is herefore heoreically ambiguous and becomes an empirical quesion. The use of only firs differences or percen changes in he esimaion of equaion (1) has yielded some raher ineresing resuls. Formby, e. al. (2001) esimaed equaion (1) over he period 1961 o 1996 (annual daa) and uilized wo ineracion erms in order o deermine wheher he effec ha economic growh had on changes in overall povery was differen during he economic expansions of he 1960s (1962-1972) and he 1980s (1983-1989), relaive o he oher years in he sample. The coefficien on he 1960s economic expansion ineracion erm was negaive and saisically significan, while he coefficien on he 1980s ineracion erm was saisically insignifican. Thus, during he economic expansion of he 1960s, he effec of srong economic growh on changes in
9 povery was greaer han i was in he 1980s and he resul of robus economic growh in he 1980s on changes in povery was no saisically differen from zero. Formby, e. al. (2001) also found ha neiher a percenage change in ransfer paymens nor in he number of female-headed households had a saisically significan effec on changes in he povery rae. These are ineresing resuls, since i is well documened ha a singleearner family is more likely o be in povery han a muliple earner family. The auhors reason for he saisical insignificance of he number of female-headed households is wha hey believe o be he use of a wrong variable. Raher han he number of femaleheaded households, he number of never-married female heads was used, since hey are a demographic group wih he highes povery raes. However, when uilizing his new variable, hey sill could no find a saisically significan relaionship. As far as ransfer paymens are concerned, he auhors (Formby, e. al. (2001)) simply saed ha since he sign of he coefficien is posiive bu saisically insignifican, here is no suppor for he welfare dependency hypohesis. As will be menioned shorly, i is our conenion ha hese anomalous resuls repored by Formby, e. al. (2001) and ohers may be due o he fac ha heir models are miss-specified which could lead o bias and consisency problems wih he regression esimaors. In a curren paper by Enders and Hoover (2003), a hreshold regression and a Fourier approximaion model is fi o povery-economic growh daa. 7 They conclude 7 A hreshold model incorporaes a dummy variable ha has been chosen providing he bes insample fi and avoids he danger of ex pos selecion (see Chan (1993)). A Fourier approximaion model is s 2πk 2πk y = α() + ε, where α( ) = A0 + Aksin + Bkcos. k= 1 T T s is he number of frequencies in he process α () (Enders and Hoover (2003)).
10 ha here is a large and significan effec on povery as a resul of he 1980s expansion which runs couner o he findings of previous sudies on his subjec. The auhors make he case ha heir specificaions provide a beer empirical model of povery han wha was done in prior research. However, hey also fail o ake ino accoun he possibiliy of coinegraing relaionships and as such, he resuling Fourier and hreshold model specificaions may also be miss-specified. Finally, here are problems associaed wih using he overall povery rae as he crierion variable. We use he sandard measure of povery which is formally defined in he Unied Saes in absolue erms and is measured by he number of persons wih equivalence scale adjused incomes below he Orshansky povery line (Orshansky (1965.1, 1965.2). I has been acknowledged ha ever since he influenial conribuion of Sen (1976), headcoun measures of povery are problemaic because here are oher aspecs of he income disribuion ha are ignored. For example, if only he headcoun maers, income could be redisribued from he poores of he poor o families slighly below he povery line and he official povery measure would decrease. Sen (1976) demonsraes ha when he head coun raio and average income shorfall (povery gap) of he poor are boh consan, a rise in income inequaliy among he poor necessarily increases he economic deprivaion among he poor. In heir sudy, Formby, e. al. (2001) uilizes he Sen index which is sensiive o headcoun povery, he income shorfall of he poor, and he disribuion of income among he poor (Formby, e. al. (2001)). However, use of his superior measure did no yield any subsanive differences in heir economeric resuls, e.g., he differences in magniudes and saisical significance of he coefficiens beween he equaion using absolue povery (headcoun measure) as he dependen
11 variable and he equaion using he Sen measure were virually he same. 8 Thus, here is evidence ha use of he absolue povery measure should no invalidae our resuls. An Error-Correcion Model I is our conenion ha any empirical resuls ha emanae from he esimaion of equaion (1) may be subjec o misspecificaion error. Wha is missing is he noion of an equilibrium long-run relaionship and he inroducion of pas disequilibrium as an explanaory variable in equaion (1) ha would specify he shor-run, dynamic behavior of curren variables. I is imporan o noe ha he erm equilibrium as used here does no have anyhing o do wih marke clearing or he equaliy of acual and desired quaniies. Raher, i refers o any long-run relaionship ha may exis among he nonsaionary variables, e.g., when η 1 = 0 in equaion (4) below. Engle and Granger (1987) sae ha his could be defined as any causal, behavioral, or reduced-form relaionship among commonly rending variables (Enders (2004)). Since he effec economic growh has on povery depends on he exen of inequaliy, inequaliy mus be conrolled for in any povery funcion (Adams (2002)). Our specificaion including he disequilibrium erm and Gini coefficien is, p p p p p P = γ + αη + β P + β GINI + β U + β TR + β FEM 1 Pi i GINIi i Ui i TRi i FEMi i i= 1 i= 1 i= 1 i= 1 i= 1 p p p 5 p + β UN + β IMM + β GDP + θ GDP D + ε, UNi i IMMi i i i i, j i j i= 1 i= 1 i= 1 j= 1 i= 1 (2) 8 See Formby, J.P., G.A. Hoover, and H. Kim (2001), Economic Growh in he Unied Saes:Comparisons of Esimaes Based Upon Official Povery Saisics and Sen s Index of Povery, Working Paper, Universiy of Alabama, Table II, Model 5 and 6.
12 D = 1 when 1961 1969 1 2 3 4 = 0 oherwise, D = 1 when 1971 1973, 1976 1979 D D = 0 oherwise, = 1 when 1983 1989 = 0 oherwise, = 1 when 1991 1999 = 0 oherwise, D5 = 1 when = 2000, 2002 2004 = 0 oherwise. η = ψ + ψ P + ψ GINI + ψ U + ψ TR + ψ FEM + ψ UN 1 0 1 1 2 1 3 1 4 1 5 1 6 1 = + ψ IMM + ψ GDP 7 1 8 1 (3) (4) All of he numeric variables are in naural logs which mean ha we are dealing wih approximae annual growh raes. 9 Moreover, all coefficiens may be inerpreed as elasiciies. The descripive saisics for he firs difference of each variable may be found in Appendices I and II, respecively. 10 Noe ha in addiion o series of lagged values for each variable, equaion (2) conains η 1 which represens he long-run relaionship among he variables (equaion (4)). We incorporaed more expansionary periods han has been uilized in previous sudies. The five expansionary periods are in he 1960s, 1970s, 1980s, 1990s and 2000s (as denoed in (3) above). 11 The reference or 9 growh rae is 10 11 As an example, consider P P P 1 1, P Ln( P) = Ln( P) Ln( P 1) = Ln P 1 P P P 1 P P 1 Ln = Ln 1+. P 1 P 1 P 1. Since he annual The variables were downloaded from hp:www.haverselec.com, a fee based on-line service. These periods have been idenified as expansions by he Naional Bureau of Economic Research (hp://www.haverselec.com).
13 base caegory is he recession ime periods since 1959. Thus, each of he coefficiens, θ ij, in equaion (2) above can be compared o he coefficien, β i, and wih each oher. I is imporan o noe ha we included wo explanaory variables in equaion (2) ha have no appeared in previous sudies: he unionizaion rae, UN, and he number of immigrans enering he Unied Saes, IMM. Boh of hese facors have been recenly idenified as affecing povery raes. During he period beween 1979 and 1995, lower skilled workers experienced a significan decline in real earnings relaive o heir more highly skilled counerpars. Conemporaneously, he share of workers earning poverylevel wages increased from 23.5% o 29.7% (Mishel, e al., (1997)). Freeman and Kaz (1994) demonsrae ha conrolling for oher labor supply and demand facors, insiuional deerminans such as unionizaion also played imporan roles in explaining povery. There is some conroversy as o he naure and magniude of he affec of immigraion on domesic povery raes. Daa from he 2000 Census indicae ha he U.S. povery rae fell less han one percenage poin beween 1989 and 1999, dropping from 13.1% o 12.4%. In California and New York, he povery rae was higher in 1999 han in 1989. Given he srong economy of he laer 1990s, hese were confounding figures. One explanaion for hese phenomena is a growing immigran populaion recen immigrans are likely o be poor and accoun for a growing share of he poor populaion (Camaroa (1999)). This view is by no means wihou meri; since i is rue ha he immigran share of he populaion increased over he decade and ha he incomes of immigrans are lower han naives incomes, on average. However, i is a misake o
14 conclude ha since immigraion expanded and immigrans have lower incomes, he increase in povery mus be due o immigraion. I is an empirical quesion, since immigraion may no be he only or mos imporan facor behind increases in povery. Ifθ ij < 0, hen economic growh has reduced povery more during he jh expansionary period relaive o he recessionary periods ( β ). i Moreover, if θ5 < θ4 < θ3 < θ2 < θ1, hen he impac of growh on povery during economic expansions has diminished over ime or in he vernacular of Thornon, e. al. (1978), rickle down has peered ou. Finally, we specify equaion (2) in an error-correcion form assuming ha P, GINI, U, TR, FEM, UN, IMM, and GDP are coinegraed, e.g., heir ime pahs are influenced in a saionary way by he exen of any deviaion from long-run equilibrium where α i is he speed of adjusmen parameer. Esimaion and Empirical Resuls All of he variables should be inegraed of order one ( I (1) ) or have a uni roo in order for he specificaion of equaion (2) o be valid. The resuls of performing he Phillips-Perron uni roo ess (Phillips and Perron (1988)) on each explanaory variable are presened in Table I. 12 The null hypohesis of a uni roo could no be rejeced in each case. [ Inser Table I Here ] We use he maximum eigenvalue es developed by Johansen (1996) o es for coinegraion among he variables P, GINI, U, TR, FEM, UN, IMM, and GDP. The 12 The Phillips-Perron ess are used because of he less sringen assumpions regarding he disribuion of he error erms in he uni roo model specificaions.
15 resuls are found in Table II and only one coinegraing relaionship is indicaed a α =.01. Thus, he variables povery, inequaliy, he male unemploymen rae, federal, sae, and local social welfare paymens, he number of female-headed households, he unionizaion rae, immigraion o he Unied Saes, and gross domesic produc all appear o have a common, sochasic rend. [ Inser Table II Here ] Normalizing on P, equaion (4) may be expressed as, 13 P = λ + λgini + λu + λtr + λ FEM + λgdp + λun + λ IMM + ϑ. (5) 0 1 2 3 4 5 6 7 Equaion (5) was esimaed using he Phillips and Hansen (1990) mehod which amouns o including a differenced erm a lag one, zero, and a differenced erm of lead one for each explanaory variable and correcing for serial correlaion. 14 The parameer esimaes of he relevan erms may be found in Table III. 15 [ Inser Table III Here ] All of he explanaory variables are saisically significan a mos α =.10 excep for immigraion. Remembering ha he esimaed coefficiens are elasiciies, from a hierarchical perspecive, he level of inequaliy (GINI), unionizaion (UN), and GDP, respecively, appears o be he mos dominan in explaining long-erm movemens in he povery rae. I is imporan o noe ha he above resuls may or may no hold in he shor-run ha is, for year-o- year changes in hese variables. 13 14 15 ψ i The normalizing facor is. ψ 1 This mehod conrols for serial correlaion and endogeneiy. We did no include he coefficiens of all he lead and lag erms for reasons of breviy. Complee resuls are available upon reques from he auhors.
16 The esimaion resuls of he error-correcion model (equaion (2), above) may be found in Table IV. The coefficien on he economic growh variable during he recessionary periods is saisically insignifican he implicaion being ha economic growh has no affec on povery during economic downurns. The percenage change in povery growh as a resul of a one percen increase in economic growh for each expansionary period was, 16 1960s: -2.3321 percen, 1970s: -1.5465 percen, 1980s: -1.8105 percen, 1990s: -2.1360 percen, 2000s: -2.1842 percen. Discouning he high growh rae in he 1960s, i appears from an iniial perusal of he above elasiciy coefficiens ha he effec of economic growh on povery has increased since he 1970s expansion ( ˆ θ ˆ ˆ ˆ 70 s < θ 80 s < θ 90 s < θ 00 s), leading us o anecdoally rejec he proposiion ha rickle down has peered ou (Thornon, e. al. (1978)). However, i is pruden o es he null hypohesis θ70s = θ80s = θ90s = θ00s--he resuls of which are shown on he boom of Table IV. Given he oucomes, we mus fail o rejec he null hypohesis wih a P-Value of.8776--indicaing ha here is no saisically significan difference among he elasiciy coefficiens from he 1970s o he 2000s expansions and indeed rickle down has peered ou since he 1970s. However, conrary o some previous findings, i mus be noed ha he effec of economic growh on povery during he 1980s was saisically significan and elasic in magniude a one percen increase in 16 The elasiciies are compued by adding -.1595, he coefficien of economic growh during he recessionary periods, o each ineracion coefficien for each expansionary period.
17 economic growh was associaed wih a 1.8 percen decline in povery growh during he 1980s expansion. 17 [ Inser Table IV Here ] While he male unemploymen rae, number of female-headed households, and unionizaion affec povery in he long-run, he growh in hese variables do no influence povery in he year-o-year, error-correcion equaion. As far as he growh in male unemploymen is concerned, he resul is consisen wih he imporance of a cyclical componen--he effec of changes in he male unemploymen rae on changes in povery is small when conrolling for economic growh. I is also imporan o noe ha shor run empirical resul runs couner o wha has been replicaed in pas sudies, which have found unemploymen o have a raher large and saisically significan affec on povery raes. 18 According o Thornon, e al. (1978), unemploymen is included in he model o conrol for he las hired-firs fired syndrome. Our resuls imply ha policies improving economic growh may deliver a larger bang for he buck as far as changes in povery are concerned, han labor marke policies dealing direcly wih male unemploymen raes, ceeris paribus. The explanaory variable, growh in he number of female-headed households, does no significanly affec povery growh in he shor run. As menioned previously, his variable is one of he facors ha explain long-erm movemens in povery (see Table III). This resul ha favors he long-erm is no surprising, since he rise in he number of single-paren households over he pas 50 years has been a dominan and conroversial 17 18 By elasic, we mean a more han proporionae response. See Anderson (1964), Thornon, e al. (1978), Hirsh (1980), and Formby e al. (2001).
18 facor in he composiion of povery raes. One reason given for his increase has o do wih he corresponding reducion in povery among oher demographic groups in he economy over he long-erm. Increases in Social Securiy paymens have reduced he incidence of povery among he elderly and he Supplemenal Social Securiy program, inroduced in 1973, has reduced povery among he disabled (Wenworh and Paison (2002)). Sae, local, and federal social welfare paymens do no only influence povery over he long-erm, bu changes in hese benefis also have a saisically significan and negaive impac on changes in povery over a year-o-year basis. These resuls emphasize he imporance of he role of ransfer paymens in povery reducion. In Table IV, a one percen increase in ransfers is associaed wih a.44 percen reducion in povery growh. I is ineresing o noe ha income inequaliy which is measured by he Gini coefficien is posiively relaed o povery in he long-run (Table III), bu he growh in inequaliy is inversely relaed wih povery growh in he error correcion resuls (Table IV). Thus on a year-o-year basis, increases in he growh of inequaliy are associaed wih decreases in povery growh. I was menioned previously how his relaionship could occur. A spur in echnological change would yield income gains for enrepreneurs/managers and conemporaneously improve he wages of hose a he boom of income scale much like wha occurred in he Unied Saes during he 1990s informaion echnology boom. In addiion, higher skill levels ha are required by new echnology creae a demand for advanced educaion and raining, which would generae a wider dispariy beween skilled and unskilled workers and conribue o greaer income inequaliy.
19 The decline of unionizaion has been shown in his sudy o significanly increase povery over he long-run, bu i has had no affec on povery growh in he shor-run. This is no surprise, since in he Unied Saes he demise of unions has reduced he earnings of lower-skilled workers over he long-run. However, immigraion has been shown o have no influence on povery, ceeris paribus, boh in he long and shor-erm. As menioned previously, i is a misake o conclude ha more immigrans wih lower incomes accoun for a significan amoun of he increase in povery raes, since immigraion is clearly no he mos imporan facor influencing povery. Conclusion The rickle-down effec of economic growh is an imporan issue in policy debae. Anderson (1964) hypohesized ha povery in America would become less responsive o economic growh and new policies would be needed if povery were o be reduced. He believed ha a considerable proporion of he poor were made up of children, he elderly, and he disabled who were incapable of full-ime work. These groups were simply no affeced by he povery-reducing effecs of economic growh. Blank and Card (1993) have shown ha U.S. governmen povery saisics have become less sensiive o economic growh across ime. As a consequence, growh is believed o have become less effecive as a povery-fighing ool han i was in he 1960s (Formby, e. al. (2001)). An alernaive hypohesis is ha an increasing rae of economic growh has an even greaer influence on he reducion of povery. The implicaion here is ha some workers may no be hired under normal growh condiions, bu may find increased employmen opporuniies during periods of high and susained economic growh.
20 We have found ha while increases in economic growh are indeed significanly relaed o reducions in he povery rae for all families, ceeris paribus, economic growh has become less effecive as a povery-reducing ool han i was during he 1960s. Using an appropriaely specified error-correcion model, we have shown ha economic growh has had a saisically significan and pronounced effec on povery during he economic expansions of he 1960s, 1970s, 1980s, 1990s, and 2000s, bu ha he effec has no changed significanly over ime. This is in agreemen wih some previous sudies ha have posied he effec of economic growh on changes in povery o have eiher declined or remained unchanged over ime, e.g., he mos recen being he aforemenioned analysis by Formby, e al. (2001). However, our resuls do no suppor he conenions of previous analyses ha he effec of subsanial economic growh on changes in povery was no saisically significan during he 1980s. During his period, he effec of a one percen increase in GDP growh was associaed wih a 1.81 percen decline in povery growh. In his sudy, we have formulaed a model ha is more heoreically and saisically valid han wha has been used in prior sudies. In previous analyses of he growh-povery relaionship, here has never been menion of a long run relaionship among he variables of ineres--nor has he ime series properies of he relevan variables ever been analyzed.
21 References Aaron, H. (1967), The Foundaions of he War on Povery Reexamined. American Economic Review, 57, December, pp. 1229-1240. Adams, Richard H., Jr. (2002), Economic Growh, Inequaliy, and Povery: Findings From a New Daase. World Bank Policy Research Working Paper #2972, Washingon, D.C.: World Bank, February. Anderson, W. (1964), Trickling Down: The Relaionship Beween Economic Growh and he Exen of Povery Among American Families. Quarerly Journal of Economics, 78, pp. 511-524. Andrews, D.W.K. (1993), Tess for Parameer Insabiliy and Srucural Change Wih Unknown Change Poin. Economerica, 61, pp. 821-856. Blank, R.M. (2003), Fighing Povery: Lessons from Recen U.S. Hisory. Journal of Economic Perspecives, 14(2), pp. 3-19. Blank, R.M. (1993), Why Were Povery Raes So High in he 1980s? Working Paper No. 3878, Naional Bureau of Economic Research. Blank, R.M. and D. Card (1993), Povery, income, and growh: are hey sill conneced? Brookings Papers on Economic Aciviy, 2, pp. 285-325. Bruno, Michael, Marin Ravallion, and Lyn Squire (1998), Equiy and Growh in Developing Counries: Old and New Perspecives on he Policy Issues, Vio Tani and Ke-Young Chu, ediors, Income Disribuion and High Growh, Cambridge, MA: MIT Press. Camaroa, Seven (1999). Imporing Povery: Immigraion s Impac on he Size and Growh of he Poor Populaion in he Unied Saes, Cener Paper 15, Cener for Immigraion Sudies. Deininger, Klaus and Lyn Squire (1996). A New Daa Se Measuring Income Inequaliy, World Bank Economic Review, 10(3), pp. 565-591. Deininger, Klaus and Lyn Squire (1998). New Ways of Looking a Old Issues: Inequaliy and Growh, Journal of Developmen Economics, 57(2), pp. 259-287. Dollar, David and Aar Kraay (2001), Growh is Good for he Poor. World Bank Policy Research Working Paper #2587, Washingon, D.C.: World Bank, Augus. Enders, Waler (2004). Applied Economeric Time Series, Second Ediion, John Wiley and Sons, Inc.
22 References (Coninued) Enders, Waler and Gary A. Hoover (2003), The Effec of Robus Growh on Povery: A Nonlinear Analysis. Applied Economics, 35(9), June, pp. 1063-1071. Enders, Waler and Pierre Siklos (2001), Coinegraion and Threshold Adjusmen, Journal of Business and Economic Saisics, 19(2), pp. 166-176. Engle, R.F., C.W.J. Granger (1987), Coinegraion and Error Correcion: Represenaion,Esimaion, and Tesing. Economerica, 55, March, pp. 251-276. Formby, J.P., G.A. Hoover, and H. Kim (2001), Economic Growh in he Unied Saes: Comparisons of Esimaes Based Upon Official Povery Saisics and Sen s Index of Povery. Working Paper, Universiy of Alabama. Freeman, R. B. and L.F. Kaz (1994). Rising wage inequaliy: he Unied Saes vs Oher Advanced Counries, in Working Under Differen Rules, (Ed.), R. B. Freeman, Russell Sage Foundaion, New York, pp. 29-62. Hirsch, Barry T. (1980), Povery and Economic Growh: Has Trickle Down Peered Ou? Economic Inquiry, 18, pp. 151-157. Johansen, Soren (1996). Likelihood-Based Inference in Coinegraed Vecor Auo- Regressive Models, Oxford: Oxford Universiy Press. Kuznes, Simon (1995). Economic Growh and Income Inequaliy, American Economic Review, March, pp. 1-28. MacKinnon, James G., Alfred A. Haug, and Leo Michelis (1999). Numerical Disribuion Funcions of Likelihood Raio Tess For Coinegraion, Journal of Applied Economerics, 14, pp. 563-577. Mishel, L., J. Bernsein, and J. Schmi, (1997). The Sae of Working America: 1996-97, M.E. Sharpe, New York. Orshansky, M. (1965.1). Couning he poor: anoher look a he povery profile, Social Securiy Bullein, 28, 387-406. Orshansky, M. (1965.2). Who s who among he poor? a demographic view of povery, Social Securiy Bullein, 29, pp. 3-32. Perl, L. and L. Solnick (1971), A Noe on Trickling Down. Quarerly Journal of Economics, 85, February, pp. 171-178.
23 References (Coninued) Phillips, Peer, and Bruce Hansen (1990). Saisical Inference in Insrumenal Variables Regression wih I(1) Processes, Review of Economic Sudies, 57, pp. 99-125. Phillips, P. and P. Perron (1988), Tesing for a Uni Roo in Time Series Regression. Biomerica, 75, June, pp 335-346. Plonick, R. and F. Skidmore (1975), Progress Agains Povery. New York: Academic Press. Ravallion, Marin (1995). Growh and Povery: Evidence for Developing Counries in he 1990s, Economic Leers, 48, June, pp. 411-417. Recor, R. and W. Lauder (1995), America s Failed $5.4 Trillion War On Povery. Washingon, D.C.: The Heriage Foundaion. Sen, A.K. (1976). Povery: an ordinal approach o measuremen, Economerica, 44, pp. 219-231. Squire, Lyn (1993). Fighing Povery, American Economic Review, May, pp. 377-382. Sock, J.H. and M.W. Wason (1993). A Simple Esimaor of Coinegraing Vecors in Higher Order Inegraed Sysems, Economerica, 61, pp. 783-820. Thornon, J.R., R.J. Agnello, and C.R. Link (1978), Povery and Economic Growh: Trickle Down Peers Ou. Economic Inquiry, 26, pp. 385-394. Wallace, G. and R.M. Blank (1999), Wha Goes Up Mus Come Down. Explaining Recen Changes in Public Assisance Caseloads. Economic Condiions and Welfare Reform, Sheldon H. Danziger, edior. Kalamazoo, MI: W.E. Upjohn Insiue for Employmen Research. Wenworh, Seyda G. and David Paison (2001), Income Growh and Fuure Povery Raes of The Aged. Social Securiy Bullein, 64(3), pp. 23-37.
24 Appendix I Daa Sources Variable Years P - Povery Rae, All Families (%) 1959-2004 GINI - Gini Coefficien 1947-2004 U - Male Unemploymen Rae (%) 1948-2004 TR - Federal, Sae and Local Social Welfare Paymens (Bil. 2000 $) 1946-2004 FEM - Number of Female Headed Households (000s) 1947-2004 UN - Union Membership as a Percenage of Toal 1948-2004 Wage and Salary Workers (%) IMM Immigraion o he Unied Saes 1929-2004 GDP - Gross Domesic Produc (Chained) (Bil. 2000 $) 1929-2004
25 Appendix II Descripive Saisics Naural Log of Firs Differences (Annual Growh Raes) P GDP GINI U Mean 2.631779 14.93831-0.966198 1.640681 Median 2.591509 15.05145-0.994256 1.661398 Maximum 3.109061 16.19094-0.825536 2.295896 Minimum 2.406945 13.36209-1.055553 1.017643 Sd. Dev. 0.188075 0.813470 0.073341 0.311492 TR FEM UN IMM Mean 5.355608 9.678216 3.087419 12.52519 Median 5.740568 9.751503 3.193975 12.74361 Maximum 6.604288 10.41277 3.548139 14.41828 Minimum 3.699411 8.695841 2.495859 10.04620 Sd. Dev. 0.924414 0.535403 0.341968 1.097665
26 Null Hypohesis: Variable has a Uni Roo Table I Phillips-Perron Uni Roo Tess Variable PP Tes Saisic P Value Log of Povery Rae -2.08.54 Log of Gini -1.86.66 Log of Male Unemploymen Rae -3.14.11 Log of Real Sae, Local, and Federal Social Welfare Paymens -1.01.93 Log of Number of Female-Headed Households.22.99 Log of Union Membership as Percen of Wage and Salary Workers -3.01.14 Log of Immigraion o he Unied Saes -.88.79 Log of Real Gross Domesic Produc -2.58.29
27 Table II Johansen Maximum Eigenvalue Tes H 0 1 : r H : r+ 1 Hypohesized Max-Eigen 0.01 No. of CE(s) Eigenvalue Saisic Criical Value Prob.** None * 0.843713 81.66675 58.66895 0.0000 A mos 1 0.666880 48.36709 52.30821 0.0291 A mos 2 0.579551 38.12302 45.86900 0.0817 A mos 3 0.435076 25.12682 39.37013 0.3765 A mos 4 0.368767 20.24352 32.71527 0.3246 A mos 5 0.260034 13.25068 25.86121 0.4294 A mos 6 0.206228 10.16220 18.52001 0.2015 A mos 7 0.023522 1.047355 6.634897 0.3061 Max-eigenvalue es indicaes 1 coinegraing eqn(s) a he 0.01 level * denoes rejecion of he hypohesis a he 0.01 level **MacKinnon-Haug-Michelis (1999) p-values
28 Table III Regression Resuls (All Variables are Expressed as Naural Logarihms) Dependen Variable: P Sample (adjused): 1960-2004 Included observaions: 45 afer adjusmens Variable Coefficien Sd. Error z-saisic Prob. Inercep 11.68012 4.030470 2.897954 0.0038 GINI 0.723588 0.299369 2.417049 0.0156 U 0.226129 0.044214 5.114388 0.0000 TR -0.288362 0.134862-2.138208 0.0325 FEM 0.247462 0.101919 2.428026 0.0152 UN -0.638389 0.235538-2.710346 0.0067 IMM 0.010755 0.021991 0.489053 0.6248 GDP -0.505064 0.293362-1.721641 0.0851 Adjused R-squared 0.970262 S.E. of regression 0.030305 Durbin-Wason sa 2.017452 F-saisic 144.5588 Prob (F-saisic) 0.000000
29 Table IV Error Correcion Model Esimaion Resuls Dependen Variable: P Sample (adjused): 1961-2004 Included observaions: 44 afer adjusmens Variable Coefficien Sd. Error -Saisic Prob. Inercep 0.067519 0.026357 2.561692 0.0159 ˆ η 1-0.135979 0.053813-2.526880 0.0115 P 1 0.142930 0.230239 0.620788 0.5396 GINI 1-0.936426 0.501367-1.867746 0.0719 U 1-0.018767 0.103693-0.180983 0.8576 TR 1-0.446039 0.217118-2.054358 0.0491 FEM 1 0.192089 0.472463 0.406569 0.6873 UN 1-0.025653 0.432582-0.059301 0.9531 IMM 1-0.015518 0.034846-0.445329 0.6594 GDP 1-0.159508 0.831281-0.191882 0.8492 D60S* GDP 1-2.172555 0.542406-4.005401 0.0004 D70S* GDP 1-1.386961 0.539220-2.572162 0.0155 D80S* GDP 1-1.650983 0.527815-3.127956 0.0040 D90S* GDP 1-1.976442 0.732275-2.699044 0.0115 D00S* GDP 1-2.024721 0.912242-2.219500 0.0344 Adjused R-squared 0.576059 S.E. of regression 0.035101 Durbin-Wason sa 2.268277 F-saisic 5.173519 Prob (F-saisic) 0.000093 H θ θ θ θ 0 : 70s = 80s = 90s = 00s Wald Tes: Chi Square =.6813, df = 3 Prob = 0.8776