Unemployment and Hysteresis: A Nonlinear Unobserved

Transcript

Unemployment and Hysteresis: A Nonlinear Unobserved
Components Approach (Studies in Nonlinear Dynamics
& Econometrics, 25(1) 2011, forthcoming)
Silvestro Di Sanzo
and
U¢ cio Studi Confcommercio
Silvestro Di Sanzo
and
Alicia Pérez-Alonso
Universidad Carlos III de Madrid
Alicia Pérez-Alonso (U¢ cio Studi Confcommercio
Universidad Carlos1III
/ 19
de M
1. Research objective
Stylized fact
Fact
Observed Unemployment (U) persistence in European countries.
Examples
Transition European Unemployment: 70’s (1-2%) to 90’s (10-15%).
Euro area seasonally-adjusted Unemployment: 7.5% (September 2008).
Silvestro Di Sanzo
and
/ 19
de M
Two main approaches in the literature
Natural rate theory: Cyclical unemployment and natural
unemployment evolve independently (Freedman 1968; Bean et al.
1987; Layard et al. 1991).
Unemployment Hysteresis theory: Cyclical unemployment and
natural unemployment do not evolve independently (Amable et al.
1995; Røed 1997). Hysteresis arises when a change in the cyclical
unemployment induces a permanent change in the natural rate.
Silvestro Di Sanzo
and
/ 19
de M
Empirical literature
Explanations as to why Hysteresis can arise:
Human Capital: long term U leads to a depreciation of individual
skills and a demoralising e¤ect on search behaviour contributing to a
less e¢ cient matching process (Phelps 1972; Pissarides 1992).
Physical Capital: Existence of …xed and sunk cost, which make
current U a function of past labour demand (Bean 1989; Cross 1995).
Insider-oustsider models of wage bargaining: Given the presence
of turnover costs, a shock that reduces the number of insiders one
period raises the optimal insider-wage in subsequent periods, which
prevents unemployed workers from being hired. When insider status
= current employment ) employment follows a RANDOM WALK
(Blanchard and Summers 1986; Lindbeck and Snower 1988).
Result: Model U series as a linear ARMA-type process and check for
the presence of a unit root (Røed 1997).
Limits: Natural and cyclical shocks are summarized in the innovation
with no distinction.
Silvestro Di Sanzo
and
/ 19
de M
Empirical Literature
Jaeger and Parkinson (1994, JP): Discriminate between natural and
cyclical shocks by means of a Unobserved Components Model.
Limits: This approach does not take into account the possible
existence of nonlinear dynamics in U series.
Theoretical evidence suggests that U has to be able to account for
nonlinearity:
Asymmetric Adjustment costs of labour (Johansen 1982; Bentolila and
Bertola 1990; Hamermesh and Pfann 1996).
Asymmetry in job creation and destruction (Mortensen and Pissarides
1993; Caballero and Hammour 1994).
Asymmetry in capital destruction (Bean 1989).
Silvestro Di Sanzo
and
/ 19
de M
Empirical Literature
Empirical Evidence for nonlinarity:
Nonparametric techniques (Neftci 1984; Sichel 1989; Rothman 1991).
Parametric nonlinear TS models: Hansen 1997; Bianchi and Zoega
1998; Koop and Potter 1999; Papell et al. 2000; Caener and Hansen
2001; Skalin and Terarsvirta 2002; Coakley and Fuertes 2006; Caporale
and Gil-Alana 2007 (MS, TAR or STAR speci…cations).
We extend JP’s model by introducing nonlinearities using a TAR
model (Petruccelli 1992).
Silvestro Di Sanzo
and
/ 19
de M
Outline for the rest of the talk
2. Jaeger and Parkinson’s model
3. An extension of Jaeger and Parkinson’s model
4. Hysteresis Hypothesis
4.1 Testing strategy
5. Empirical results
6. Concluding remarks
Silvestro Di Sanzo
and
/ 19
de M
2. Jaeger and Parkinson’s model
Decomposition into Unobserved Components: Ut = UtN + UtC
Natural equation:
UtN = UtN 1 + αUtC
1
+ eNt
Cyclical equation:
UtC = φ1 UtC
1
+ φ2 UtC 2 + eCt
Identi…cation equation:
Dt = βDt
1
+ δUtC + eD
t
Assumptions about the error term:
0
0
(eNt , eCt , eD
t )
σ2N
N@ 0
0
Estimation methodology: Kalman Filter
Silvestro Di Sanzo
and
0
σ2C
0
1
0
0 A
σ2D
/ 19
de M
3. An extension of Jaeger and Parkinson’s model
Decomposition into Unobserved Components: U = UtN + UtC
Natural equation:
UtN =
UtN 1 + α1 UtC
UtN 1 + α2 UtC
+ eNt
N
1 + et
1
Cyclical equation: UtC = φ1 UtC
if Ut
if Ut
1
1
Ut
Ut
d
d
γ
with d 2 f2, 3g
<γ
+ φ2 UtC 2 + eCt
Identi…cation equation: Dt = βDt 1 + δUtC + eD
t
Assumptions about the error term:
0 2
1
σN 0
0
0
σ2C 0 A
(eNt , eCt , eD
N@ 0
t )
0
0
σ2D
1
Estimation methodology: Threshold Kalman Filter (Grid search
over (γ, d ))
Silvestro Di Sanzo
and
/ 19
de M
Jaeger and Parkinson’s model:
H0JP : α = 0.
Extended model:
H0 : α1 = α2 () Linearity test
Problem (Hypothesis testing when a nuisance parameter is not
identi…ed under H0 )
(γ, d ) are not identi…ed under H0 =) The asymptotic distribution of
standard tests is unknown.
Solution
We propose to approximate the distribution of the test statistic of interest
by a consistent bootstrap procedure (Sto¤er and Wall, 1991).
Silvestro Di Sanzo
and
Universidad Carlos
10III
/ 19
de M
Testing strategy
If we reject
NONLINEAR HYSTERESIS
If we DO NOT reject
Estimate JP’s model
H0 : α 1 = α 2
H0JP : α = 0
Silvestro Di Sanzo
and
If we reject
LINEAR HYSTERESIS
If we DO NOT reject
NO HYSTERESIS
Universidad Carlos
11III
/ 19
de M
Data (OECD Main economic indicators): U (unemployment;
seasonally adjusted) and GDP (real gross domestic product;
seasonally adjusted + natural logs)
Italy (1970:1-2007:2); France (1978:1-2007:2); U.S. (1965:1-2007:2).
Unit Root Tests for GDP and U:
Table 1: Unit Root Tests
p-value of ADF test on GDP series
Italy
0.9970
France
0.2622
U.S.
0.9459
p-value of Caner and Hansen’s test on Unemployment series
Italy
0.002
France
0.001
U.S.
0.000
Silvestro Di Sanzo
and
Universidad Carlos
12III
/ 19
de M
(I)
Tests for Hysteresis* (USA: WB; France and Italy: RB)
Table 2 : Tests for the Hysteresis Assumption
Nonlinear Model
Linear Model
H0JP : α = 0
Italy
Bootstrap p-value=0.0021
p-value=0.269
France
p-value=0.285
U.S.
p-value=0.405
*WB=wild bootstrap; RB=residual bootstrap
H0 : α 1 = α 2
**Signi…cant at 1%
Silvestro Di Sanzo
and
Universidad Carlos
13III
/ 19
de M
(II)
Table 3 : Estimation Results for the nonlinear model of ITALY
% of observations
i = 1 (41%)
i = 2 (59%)
Natural Rate Equation
i =1
i =2
αi
2.512 (0.101) 1.476 (0.042)
σN
0.431 (0.021)
Cyclical Rate Equation
1.521 (0.187)
0.638 (0.050)
0.020 (0.004)
φ1
φ2
σC
Identi…cation Equation
β
δ
σD
Threshold [boot. 90% con…dence]
Silvestro Di Sanzo
Delay lag
and
0.463 (0.023)
5.401 (1.211)
0.640 (0.035)
γ = 0.1 [0.023, 0.247]
d =2
Universidad Carlos
14III
/ 19
de M
(III)
Table 4 : Estimation Results for the nonlinear model of FRANCE
% of observations
i = 1 (44%)
i = 2 (56%9
i =1
i =2
αi
3.540 (0.913)
1.570 (0.022)
σN
0.416 (0.035)
1.615 (0.041)
0.733 (0.056)
0.139 (0.074)
φ1
φ2
σC
β
δ
σD
Silvestro Di Sanzo
Delay lag
and
0.600 (0.069)
0.390 (0.052)
0.540 (0.033)
γ = 0.16 [0.123, 0.532]
d =3
Universidad Carlos
15III
/ 19
de M
(IV)
Table 5 : Estimation Results for the nonlinear model of U.S.
% of observations
i = 1 (42%)
i = 2 (58%)
i =1
i =2
αi
1.343 (0.121) 0.562 (0.022)
σN
0.400 (0.018)
1.237 (0.082)
0.650 (0.089)
0.120 (0.023)
φ1
φ2
σC
β
δ
σD
Silvestro Di Sanzo
Delay lag
and
0.611 (0.042)
1.626 (0.0159)
0.690 (0.031)
γ = 0.3 [0.143, 0.632]
d =2
Universidad Carlos
16III
/ 19
de M
Silvestro Di Sanzo
and
(V)
Universidad Carlos
17III
/ 19
de M
(I)
Empirical results:
Hysteresis is found in IT, FR and U.S. ) JP not discarded on
theoretical grounds but on empirical grounds.
For IT, FR and U.S.: Asymmetric responses of U N as regards U C
movements () U N does not decrease in FAVORABLE cyclical
periods as much as it increases in UNFAVORABLE ones.
U.S.: Periods of increasing natural rate correspond (lagged) to the
NBER recession periods. Consistent with U as a lagging indicator at
troughs. Turning Points for IT and FR derived using Harding and
Pagan (2002).
Implications for policy-makers.
Our contribution:
Extension of JP model by introducing nonlinearities using a TAR
model.
Two bootstrap mechanisms, RB and WB, to calculate an appropriate
p-value for the linearity test.
Silvestro Di Sanzo
and
Universidad Carlos
18III
/ 19
de M
(II)
Our …ndings have three important implications.
Firstly, our empirical evidence supports theoretical models of
hysteresis that describe it as a nonlinear phenomenon (see Bentolila
and Bertola 1990, and Caballero and Hammour 1994 among others).
Secondly, since statistical linear models are not able to describe the
dynamic asymmetries of the unemployment rate, nonlinear models are
needed to correctly represent and test hysteresis phenomena. Here,
JP’s hysteresis test may lead to obtain misleading inference results.
Thirdly, our results are important for policy-makers. When hysteresis
is present in the labour market, monetary policies, traditionally
considered as ine¤ective, can be used to combat unemployment
without immediate in‡ationary consequences. This evidence is in
contrast with non-accelerating in‡ation rate of unemployment
(NAIRU) models where shocks are not long-lived, and thus the
unemployment rate reverts back to its underlying equilibrium level
(see Friedman 1968).
Silvestro Di Sanzo
and
Universidad Carlos
19III
/ 19
de M

Unemployment and Hysteresis: A Nonlinear Unobserved

Transcript

Documenti analoghi

DpeRTrMEl.{To Dr Sruur Polrrrcr

Contratti affitti spazi MM

Alicia Giménez Bartlett

alghero Angedras Capodanno 2015

Cineplaza a Briga, Picciotto: «Importanza delle periferie»

Locandina REDES - Dipartimento di Lingue e letterature straniere

27/10/2015 RAI 3 TG3 LOMBARDIA - 19.35

confcommercio agrigento contro la chiusura dell`unico sportello

Scarica il comunicato - Unione Confcommercio Milano