Explaining unemployment rates in several European countries - a panel data approach

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1 UK Ökonometrsche Methoden für Paneldaten Prof. Robert Kunst LV Nummer: Explanng unemployment rates n several European countres - a panel data approach Helene Dearng Rchard Sellner Stefan Worel

2 . Introducton In a panel data analyss we try to explan unemployment rates n several European Countres. Snce growng unemployment rates are ncreasngly part of the polcal debate n Europe, we nvestgate the determnants of the progresson of unemployment rates. Unemployment s a complex phenomenon dependng on a varety of factors ncludng wage barganng, globalsaton, busness cycle, unon power, human resources, productvy and labour market msmatch. A lot of factors are determned at the sectoral level, whch s not covered n ths study. The am of ths study s the proper use of panel data methods learned n the lecture Econometrc Methods of Panel Data, especally the choce of an adequate specfcaton.. Data We obtaned data from the EUROSTAT database. Our sample comprses European countres over a perod from 995 to 005. The countres ncluded are: Belgum, Bulgara, Czech Republc, Denmark, Germany, Estona, Ireland, Span, France, Italy, Latva, Lhuana, Luxembourg, Hungary, The Netherlands, Poland, Slovaka, Fnland, Sweden, UK and Norway. We used the followng varables: employment, unemployment, populaton, gdp, government fnal consumpton, government expendure for educaton and prce ndex (995=00). All monetary data are n mllon EUROS and data on employment, unemployment and populaton s n,000 people. Usng ths varables we calculated average labour productvy, unemployment rates, government fnal consumpton per capa, government expendure for educaton per capa and nflaton. Further we took frst log-dfferences for all varables. Due to a lack of data we excluded Bulgara and the varable government expendure on educaton. GDP measured at constant 995 prces and exchange rates.

3 . Model and Method Our general model s: u = f( alp, gdp, govcpc, nf) () where u s unemployment rate, alp s average labour productvy, govcpc s government fnal consumpton per capa, nf s nflaton and s the dfference operator. Frst, the pooled OLS specfcaton was estmated: u = α + alp + gdp + govcpc + nf + ε =,..., N, t =,..., T, ε ~ N(0, σ ) () 4 Snce we assume that there are country ndvdual effects, we mght use one-way fxed-effect (see equaton ()) or random-effect estmators (see equaton (4)). Indvdual effects may capture unon densy, nstutonal settngs and mnmum wage. Those effects are otherwse not captured and may result n omted varable bas. u = α + alp + gdp + govcpc + nf + ε 4 ε = µ + ν, ν ~ N(0, σ ),..., N =, t =,..., T () u = α + alp + gdp + govc + nf + ε ε = µ + ν, µ ~ N(0, ), ν ~ N(0, σ ν ) σ µ,..., N 4 =, t =,..., T (4) In another specfcaton we control for possble tme effects lke busness cycles or supply shocks. The two-way fxed-effect model s specfed as follows: u = α + alp + gdp + govcpc + nf + ε 4 ε = µ + λ + ν, ν ~ N(0, σ ) t,..., N =, t =,..., T (5) The formal specfcaton for the two-way random-effects model s: u = α + alp + gdp + govcpc + nf + ε 4 ε = µ + λt + ν, µ ~ N(0, σ µ ), λt ~ N(0, σ λ ), ν ~ N(0, σ ν ) =,..., N, t =,..., T (6)

4 We expect a posve relaton between the growth of unemployment rates and change n average labour productvy, snce f workers are more productve, hgher wages are expected, whch may lead to less labour demand and therefore hgher unemployment. Growth of gdp s assumed to decrease growth n unemployment. An ncrease n government fnal consumpton growth should decrease growth n unemployment, as nvestments n nfrastructure (typcal government expendure) are supposed to generate addonal employment. An ncrease n nflaton rate s supposed to decrease the growth n unemployment due to the negatve relaton postulated by the Phllps Curve.

5 4. Results In ths secton the results of varous estmaton specfcatons are shown. The precedng equatons have been estmated usng Evews 5.0. The sample ncludes 0 countres and 9 perods of observaton. Table : Estmaton output for pooled OLS regresson (Equaton ) Dependent Varable: u Method: Pooled Least Squares Varable Coeffcent Std. Error t-statstc Prob. α R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regresson Akake nfo creron Sum squared resd.054 Schwarz creron Log lkelhood F-statstc.7980 Durbn-Watson stat.6840 Prob(F-statstc)

6 Table : Estmaton output for the one-way fxed-effects model (Equaton ) Dependent Varable: u Method: One-way fxed effects model Varable Coeffcent Std. Error t-statstc Prob. α Fxed Effects (Indv.) _BE.8E-05 _CZ _DK _DE _EE _IE _ES _FR _IT _LV _LT _LU 0.9 _HU _NL _PL _SK _FI _SE _UK _NO R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regresson Akake nfo creron Sum squared resd Schwarz creron Log lkelhood F-statstc Durbn-Watson stat.496 Prob(F-statstc)

7 Table ; Estmaton output for one-way random-effects model (Equaton 4) Dependent Varable: u Method: Pooled EGLS (Indvdual random effects) Wansbeek and Kapteyn estmator of component varances Varable Coeffcent Std. Error t-statstc Prob. α Random Effects (Indv.) _BE _CZ _DK _DE _EE _IE _ES _FR _IT _LV _LT _LU _HU _NL _PL _SK _FI _SE _UK _NO Effects Specfcaton Indvdual random S.D. / Rho Idosyncratc random S.D. / Rho Weghted Statstcs R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regresson Sum squared resd.65 F-statstc Durbn-Watson stat.0485 Prob(F-statstc)

8 Table 4: Estmaton output for two-way fxed-effects model (Equaton 5) Dependent Varable: u Method: Two-way fxed-effects model Varable Coeffcent Std. Error t-statstc Prob. α Fxed Effects (Indv.) _BE _CZ _DK _DE _EE _IE _ES _FR _IT _LV _LT _LU _HU _NL _PL _SK _FI _SE _UK _NO Fxed Effects (Tme) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regresson Akake nfo creron Sum squared resd.65 Schwarz creron -.84 Log lkelhood F-statstc Durbn-Watson stat Prob(F-statstc)

9 Table 5: Estmaton output for two-way random-effects model (Equaton 6) Dependent Varable: u Method: Pooled EGLS (Two-way random effects) Wansbeek and Kapteyn estmator of component varances Varable Coeffcent Std. Error t-statstc Prob. α Random Effects Indvdual Coeffcent Tme Coeffcent _BE _CZ _DK _DE _EE _IE _ES _FR _IT _LV _LT _LU _HU _NL _PL _SK _FI _SE _UK _NO Effects Specfcaton Indvdual random S.D. / Rho Tme random S.D. / Rho Idosyncratc random S.D. / Rho Weghted Statstcs R-squared Mean dependent var Adjusted R-squared S.D. dependent var 0.96 S.E. of regresson Sum squared resd.6045 F-statstc Durbn-Watson stat Prob(F-statstc)

10 In general the sgns of the coeffcents ndcate a posve relaton between growth n unemployment rates and growth n average labour productvy and a negatve nfluence of gdp growth and change n nflaton on growth n unemployment rates. These confrm the ntuve assumptons about these relatons. Only the sgn of the coeffcent of government fnal consumpton s counterntuve. Ths mght be due to the fact, that our conjecture about the composon of government consumptons s not correct.

11 Poolably Tests The frst poolably test has the OLS model as null and the one-way FE-model as alternatve hypothess: 0: µ = 0, =,,..., N H The correspondng F-statstc s gven by: F ( R R )/( N ) ur r = ~ F N, N( T ) K ( Rur)/( NT N K) We receve a F 9, 76 value of. whch s well above the crcal value of.. We can reject the null hypothess that the ndvdual effects are zero and therefore consder the FE-model. As a next step we construct a poolably test wh the null hypothess of a one-way FE-model and alternatve hypothess of a FE two-way model: H : λ 0, =,,..., N 0 = The F-statstc s gven as follows: F ( R R )/( T ) ur r = ~ F T,( N )( T ) K ( Rur)/(( N )( T ) K) The value for F 9, 67 s.8 whch s below the crcal value of.4. Therefore we tend to choose the one-way FE model. Fnally we carred out a Hausman-Wu Test to decde whether to use the fxed effects or random effects specfcaton. The statstc reads as follows: m = q'(varq) ~ ~ q, q = ˆ, varq = var var ˆ where ˆ ( ~ ) are the coeffcents of the random (fxed) effects model. Ths statstc s χ ( k ) dstrbuted under the null hypothess. The H 0 s that the dfference n coeffcents s not systematc. We receve an m of.4 whch rejects ths null, so we should use the fxed effects model.

12 5. Summary and concluson We nvestgated the determnants of growth n unemployment rates across Europe whn a panel data approach. As ndependent varables we ncluded frst logged dfferences of the average labour productvy, gdp growth, government fnal consumpton and nflaton rates. All coeffcents except for government fnal consumpton show the expected sgn and are hghly statstcally and economcally sgnfcant. Our assumpton that government fnal expendure protects a country from ncreasng unemployment rates was rejected emprcally. Possble reason may be endogeney wh gdp growth and wrong assumptons about the composon of our measure. Panel specfcaton tests such as smple poolably F-Tests and the Hausman-Wu Test are n favour of the one-way fxed-effects model, whch s n lne wh our expectaton, as growth n unemployment rates s assumed to dffer sgnfcantly across countres.

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