비대칭 GARCH 모형을 이용하여 · 2017-01-31 · 2 金融硏究 제23권 제2호 2009 theory)의 핵심적인 내용을 이루고 있다.1) Merton(1973)의 Intertemporal CAPM

1

||||||| Journal of Money and Finance | Vol.23 | No. 2 | 2009. 6 1)

: GARCH

*

. ,

(risk premium) , (risk averseness),

(asymmetric volatility) .

, EGARCH-M

, .

, .

.

: , , ,

JEL : C32, E32, G12

.

(risk averseness parameter) ( )

(risk premium = - )

CAPM(capital asset pricing model) (asset pricing

* (Tel : 02-3277-4467, E-mail : [email protected])

2 23 2 2009

theory) .1) Merton(1973) Intertemporal CAPM

(+) ,

(+) (-)

. (tradeoff)

, . Kim

and Lee(2008) , (risk-aversion)

(state-dependent),

.

,

(+) .

(time-varying) ,

.2)

(asymmetric volatility) (business cycle)

. , EGARCH-M -

, - .

.

, ( )

.

.

.

(intertemporal substitute relation)

1) CAPM Consumption CAPM , CAPM

U = E(R)-A2( E(R) : , 2 : , A : ) Consump-

tion-CAPM Constant Relative Risk Averseness(CRRA) (

C : ) A

. A . 2) Kim and Lee(2008) .

3

. , French, Schwert and Stambaugh

(1987) Campbell and Hentschel(1992) (+)

, Fama and Schwert(1977), Campbell(1987), Breen, Glosten, and

Jagannathan(1989), Turner, Startz and Nelson(1989), Pagan and Hong(1991), Nelson, Glosten,

Jagannathan and Runkle(1993), Whitelaw(2000) (-) . Harvey

(1989)

. (volatility feedback)

. Brown(1988)

, . , Potera and Summers(1986)

. French, Schwert and

Stambaugh(1987) (shock return) (innovation)

(-) . Haugen, Talmor, and Torous(1991)

.

(asymmetric)

. ,

(-) . ,

. Black(1976) (leverage)

. Christie(1982), Schwert

(1989)

.

, . Engle, Lilien,

and Robin(1987) ARCH (

) ARCH-M .

Engle(1982) Bollerslev(1986) GARCH-M .3)

3) GARCH (moving average)

(persistence) . Attannasio

and Wadhwani(1989), Chou(1988)

GARCH .

4 23 2 2009

French, Schwert, and Stambaugh(1987) GARCH-M

(+) . Chou(1988) GARCH-M

(-) ,

.

. , Schwert(1990) Fama(1990)

. McQueen and Roley(1993)

(stage) .

. Hamilton and Lin(1996) (state)

(Markov Chain)

.

Whitelaw(1994)

(unconditional contemporaneous relation) ,

(non-contermporaneous relation) .

,

. Wu(2001) (moment method)

. DeGoeji and Marquering(2002) GARCH

(Treasury bond)

.

. Duffe(2005) (wealth)

,

. Li(2007, 2008)

(Consumption Asset Pricing Model)

(equity premium puzzle)

. Lundblad(2007)

. Mele(2007)

5

(countercyclical)

, -

.

,

, Fama and French(1989)

(IP) . Kim and Lee(2008) NBER

(boom) (recession) .4)

GARCH

-, , -

. (+),

(-) ,

.

,

,

.

, , (1993) GARCH(1, 1)-M MA(1)-

GARCH(1, 1)-M , . (1994)

ARCH(3)-M GARCH(1, 1)-M

. (1999)

, GARCH

7

. (2002)

, GJR-GARCH

-, ,

, .

4) NBER employment, sales, income, industrial production(IP)

, NBER business cycle()

. .

6 23 2 2009

. , (1999) , ,

(2005) (symmetric)

(asymmetric) ,

. (good news) (bad

news) .

(1999)

.

,

. (2002) 9.11

. (2003)

, , ,

. (2005) Markov- Switching ARCH

, .

13

. (2008) AR(1)-GARCH(1, 1)

.

KOSPI .

(2009) (Consumption Asset Pricing Model)

1978 2008 .

.

,

, .

,

.

Kim and Lee(2008) (risk

averseness) (procyclical) ,

, 3

.

7

Kim and Lee(2008) Kim

and Lee(2008) ,

, 3 3

. , , , 3 ,

3 .

.

, AR(1)-EGARCH(1, 1)-M

. ,

. .

.

1. EGARCH-M

EGARCH-M 5)

(time-varying)

,

.

(specification test) (parsimo-

nious) AR(1)-EGARCH(1, 1)-M .6)

(stationarity condition) (unit root

5) Engle and Ng(1993) GARCH ARCH

EGARCH .

EGARCH .6) AR(p) p .

(Akaike Information Criterion : AIC)

p = 1 . AR(p) ARCH

Ljung-Box (autocorrelation)

. , KOSPI

p-value = 0.96 ,

p-value = 0.00 GARCH .

8 23 2 2009

test) , .7)

AR(1)-EGARCH(1, 1)-M (1) (2) .

(1)

(2)

: (KOSPI -3 )

: (conditional variance)

(1) t (rt) t-1 (rt-1)

(t), .

(+) (-)

, ,

. (2) 1

. t (lnt) t-1 ( )

. , (fat-tail)

, t- .8)

(risk premium) .

(1) .

7) Augmented Dicky-Fuller Unit Root KOSPI () 1% ,

3 ( time trend) 5% , (KOSPI

-3 ) ( ) 1% (unit root) . 8) ,

. Jarque and Bera(1986)

(normality) , Jarque-Bera 1.2469(p-value

= 0.0000) KOSPI .

. t .

9

. (2)

EGARCH-M (asymmetry) (leverage effect)

2 (exponential) ,

(-) .

. , , ( , )

, , ( , ) ,

. t-1 , t

, (asymmetry) (leverage effect)

.

(asset pricing theory) (time varying)

, ,

. (1)

,

. 3 , ,

3 , 4 .

2. EGARCH-M

( ) () AR(1)-

EGARCH(1, 1)-M .9)

.

(3)

9) (state)

(Markov regime switching model) .

. (Markov

regime switching model)

, (state)

. ,

, (ex-post)

.

, .

10 23 2 2009

(4)

,

(3) , (constant term, )

(volatility term, ) . (, )

(volatility feedback), (risk averseness)

. (4) ()

(asymmetric volatility term, ) . ,

() (/) , .

Kim and Lee(2008) / ()

, .

() (boom) 3 , 3

1 , 0 . ()

(recession) 3 , 3 1 ,

0 . ( ) ,

.

.

: , ( = 1, = 0)

: 3 ( 3 = 1, = 0)

: 3 ( 3 = 1, = 0)

AR(1)-EGARCH(1, 1)-M (3)

(4) .

(3)

11

(4)

3

. , -

1 , 3

.

3 ,

3

. 2(6)

3(1)

.

.

1.

KOSPI 3

1 .

. 3

3

(risk-free) .10)

(1995 52008 12)

. -0.0017%(), 8.0951%()

.

10) 1 Treasury Bill . Treasury

Bill 1 . 3

.

12 23 2 2009

(non-normality) . (skewness) -0.0715 (long tail),

3.7325 (kurtosis) .

KOSPI Return(%, 1995. 52008. 12)

This figure shows dynamics of the representative Korean stock market index(or KOSPI) return from May

1995 to December 2008 on monthly basis. The data has been retrieved from Korea Exchange data archive.

-. 3

-. 2

-. 1

. 0

. 1

. 2

. 3

1 9 9 6 1 9 9 8 2 00 0 2 0 0 2 2 0 0 4 2 0 0 6 2 0 0 8

3-Year Maturity Koran Government Bond Return(%, 1995. 52008. 12)

This figure shows dynamics of the 3-year maturity Korean government bond return from May 1995

to December 2008 on monthly basis. The data has been retrieved from Bank of Korea data archive.

. 0 0 0

.0 02

.0 04

.0 06

.0 08

.0 10

.0 12

.0 14

.0 16

1996 1998 2000 2002 2004 2006 2008

13

Excess Stock Return(%, 1995. 52008. 12)

This figure shows dynamics of excess stock return(KOSPI return-3-year maturity Korean government

bond return) from May 1995 to December 2008 on monthly basis. The data has been calculated by

author from the data retrieved from Bank of Korea and Korea Exchange data archive.

- . 3

- . 2

- . 1

. 0

. 1

. 2

. 3

1 9 9 6 1 9 9 8 2 00 0 2 0 0 2 2 0 0 4 2 0 0 6 2 0 0 8

Statistic Summary of Excess Stock Return(KOSPI return-3-year maturity

Korean Government Bond Return)(1995. 52008. 12)

This table summarized basic statistics of excess stock return(KOSPI return-3-year maturity Koran

government bond return) from May 1995 to December 2008 on monthly basis. Along with the whole

period, there are 4 sub-period(boom, recession, 3-month before boom starts, 3-month before recession

starts) defined with the Korea National Statistic Office's business cycle announcement.

WholePeriod

3-month before boom

startsboom

3-month before

recession startsrecession

Number of Observation

164 18 104 18 60

average(%) -0.0017 5.9787 -1.4882 -3.7027 2.8342

standard deviation(%)

8.0950 4.9057 6.8904 10.5462 8.7347

, . ,

-1.4882%, 6.8904%. , ,

2.8342%, 8.7347% .

14 23 2 2009

, .

.

, , 3 , 3

, , . 2002

,

. ,

(coincident composite index : CCI) .

, .11)

.

, ,

.

100

100 .

(trough), (peak) .

,

. .

, .

1995 5 2008 12 (business cycle) 5 (troughs)

6 (peaks) . , 3 18, 3

18 . ,

(, ) .

3 , 5.9787% ,

11)

(CI) .

. , , ,

, ,

. ,

( ), , ,

, , , 8 .

15

4.9057% .

8.0950% . 3

, -3.7027% 10.5462%

.

Business Cycle Turning Points(1995. 52008. 12)

This table lists official troughs and peaks of Korean business cycle based on the announcement of Korea

National Statistics Office from May 1995 to December 2008 on monthly and quarterly basis. The data

is retrieved from the Korea National Statistic Offices data archive.

Trough Peak

1998. 8(I)2001. 8(III)2003. 7(III)2005. 3(I)

2006. 7(III)

1996. 5(II)2000. 8(III)

2002. 11(IV)2004. 2(I)2006. 1(I)

2008. 8(III)

Note : (I) : 1/4 Quarter, (II) : 2/4 Quarter, (III) : 3/4 Quarter, (IV) : 4/4 Quarter.

Business Cycle Coincident Composite Index(CCI)(1995. 52008. 12)

This figure shows dynamics of Korean Business Cycle Coincident Composite Index(CCI) from May 1995

to December 2008 on monthly basis. The data has been retrieved from Korea National Statistic Office

data archive.

92

94

96

98

100

102

104

106

1996 1998 2000 2 00 2 2004 2006 2008

16 23 2 2009

,

, . (-)

, (+) (+) ,

(-) . 6.8904% , 4.9057%

, 8.7347% , 10.5462% .

.

Excess Stock Return and Business Cycle(%, 1995. 52008. 12)

This figure shows dynamics of excess stock return(KOSPI return-3-year maturity Korean government bond

return) from May 1995 to December 2008 on monthly basis with business cycle changes. The gray parts

represent recession periods and the white parts represent boom period. The data has been retrieved from

Bank of Korea, Korea Exchange, and Korea National Statistics Office data archive respectively.

-.3

-.2

-.1

.0

.1

.2

.3

95 96 97 98 99 00 01 02 03 04 05 06 07

, (quarter)

, .

(frequency) , 1996 2008 50

. GARCH

t-distribution .

.

17

Excess Stock Return in the 3-month Before Boom Starts Period

(%, 1995. 52008. 12)

This figure shows dynamics of excess stock return(KOSPI return-3-year maturity Korean government bond

return) from May 1995 to December 2008 on monthly basis with business cycle changes. The gray parts

represent the 3-month before the boom periods and the white parts represent the remaining period. The

data has been retrieved from Bank of Korea, Korea Exchange, and Korea National Statistics Office data

archive respectively.

- . 3

- . 2

- . 1

. 0

. 1

. 2

. 3

9 5 9 6 9 7 9 8 9 9 0 0 0 1 0 2 0 3 0 4 0 5 0 6 0 7

Excess Stock Return in the 3-month Before Recession Starts Period

(%, 1995. 52008. 12)

This figure shows dynamics of excess stock return(KOSPI return-3-year maturity Korean government

bond return) from May 1995 to December 2008 on monthly basis with business cycle changes. The

gray parts represent the 3-month before the recession periods and the white parts represent the remaining

period. The data has been retrieved from Bank of Korea, Korea Exchange, and Korea National Statistics

Office data archive respectively.

- . 3

-. 2

-. 1

. 0

. 1

. 2

. 3

9 5 9 6 9 7 9 8 9 9 0 0 0 1 0 2 0 3 0 4 0 5 0 6 0 7

18 23 2 2009

2. AR(1)-EGARCH(1, 1)-M

AR(1)-EGARCH(1, 1)-M . 4

(, , - (d1) , 3

(d2) , 3 (d3) )

.

AR(1)-EGARCH-(1, 1)-M

() () .

() -0.0700 (-) , . ,

-0.0912 , .

AR(1)-EGARCH-(1, 1)-M (

) .

- .

() (+)

. ( )

.

. (conditional mean) (

= 1), = -0.0373 1% .

(structural break) ,

.12)

.

.

3

. 3 , ( ) 5% 0.8772

, (pre-boom) ( )

.

12) -1.4882%, 2.8342%.

19

Estimations of EGARCH-M Model with and without Business Cycle Dummy

Variable(d1)

This table summarizes estimation results of EGARCH-M with and with business cycle dummy variable

(d1). For each estimation, equations (1) and (2) are for without dummy case and (3) and (4) are for with dummy case.

EGARCH-M(Without dummy variable)

EGARCH-M(With boom-recession dummy

variable : d1)

coefficient Estimate t-value Estimate t-value

0.0061 0.3213 0.0217 0.9201

--- --- -0.0373* -2.9953

0.3425* 4.2876 0.2952* 3.4585

-0.0700 -0.2920 -0.0201 -0.0824

--- --- 0.1130 0.5813

-0.3312* -1.8211 -0.7277 -1.5243

--- --- 0.05201 0.4813

0.9254* 28.1410 0.9125* 17.2154

0.1778* 2.5073 0.4012 1.6879

-0.09142 -1.4720 -0.0601 -0.5518

--- --- -0.0001 -0.1789

Log Likelihood

197.1820 --- 199.3258 ---

Adjusted R-squared

0.1023 --- 0.1258 ---

Auto(2)Auto(6)

0.12290.0970

---0.05900.0620

---

Note : * implies significant at 5% level.

Auto(k) implies residual autocorrelation P-values.

, .

,

. 3 5.8787%

.

( ) . 3

, .

20 23 2 2009

3 (pre-boom) 1% -0.4322 .

,

.

Estimations of EGARCH-M Model with Business Cycle Dummy Variables(d2 and d3)

This table summarizes estimation results of EGARCH-M with business cycle dummy variables of (d2

and d3). The d2 is for the 3-month before the boom period and d3 is for the 3-month before the recession

period respectively. For both estimations, equations (3) and (4) show estimation specification.

EGARCH-M(3-month before boom dummy : )

EGARCH-M(3-month before recession dummy : )

coefficient Estimate t-value Estimate t-value

-0.0312* 2.1578 0.0154 1.2543

-0.0342 -0.8925 -0.0052 -0.5246

0.2992* 4.4442 0.2856* 3.8915

-0.6215* -2.8465 0.2004 0.8886

0.8772* 2.3242 -0.1356 -0.5765

-0.1351* -2.8421 -0.5886 -1.5951

-0.4934* -2.3214 0.0023 0.0022

0.9853* 185.2743 0.9612* 17.5138

-0.0683 -1.5576 0.4527* 2.5714

0.1722* 2.5675 -0.1532 -1.4281

-0.4322* -2.9689 0.0311** 1.8972

Log Likelihood

207.1409 --- 205.5146 ---

Adjusted R-squared

0.2046 --- 0.2626 ---

Auto(2)Auto(6)

0.05400.1000

---0.06800.0590

---

Note : * implies significant at 5% level.

Auto(k) implies residual autocorrelation P-values.

3

.

21

. 10% 0.0311

, .

, ( )

.

3 3

.

3 3

(asset pricing theory) .

3 164 18

. -

, Kim and Lee(2008) .

, 3 -0.1532

, .

.

3 ,

Lucas(1978) consumption asset pricing

theory . CRRA utility function,

, ( )

.13)

(5)

, , discount factor

risk premium

( ) , 3

13) Asset Pricing, Cochrane(2001) .

22 23 2 2009

( ), ( )

.

.

(

)

. Kim and

Lee(2008) Kim and Lee(2008)

, , 3

3 . ,

, , 3 , 3

.

EGARCH-M ,

.

.

Merton(1980) ()

(risk-aversion) . Kim and

Lee(2008) (procyclical)

.

, (

) .

.

.

.

.

23

, (, )

,

.

(state-dependent)

(business cycle) .

,

.

,

. Kim and Lee(2008)

,

3 .

KOSPI

, .

.

24 23 2 2009

1. , , , 10 3, 2009, 33-49.

2. , 9.11 ,

, 2002.

3. , , , 16 1, 1999, 155-170.

4. , , , 52 3, 2004, 177-207.

5. , , , 14 1, 2008, 97-117.

6. , , , 16 2, 2003, 31-65.

7. , 1995 ,

, 2007.

8. , , , 1 3, 2002, 53-96.

9. , , . 12 2, 1999, 315-340.

10. , , , , 22 2, 2005, 165-187.

11. ,

: , , , 10 1, 2005, 61-93. 12. Black, F., Studies of stock market volatility changes, Proceedings of the American

Statistical Association, Business and Economics Section 1976, 177-181.

13. Brown, Keith C., W. V. Harlow, and Seha M Tinic, Risk aversion uncertain information,

and market efficiency, Journal of Financial Economics 22, 1988, 355-385.

14. Bollerslev, T., Generalized autoregressive conditional heteroskedasticity, journal of

Econometrics 31, 1986, 307-327.

25

15. Champbell, John Y., Stock returns and the term structure, Journal of Financial

Economics 18, 1987, 373-399.

16. Chambell, John Y., and Ludger Hentchel, No news is good news, Journal of Financial

Economics 31, 1992, 281-318.

17. Chou, Ray, Volatility persistence and stock valuations : Some empirical evidence using

GARCH, Journal of Applied Econometrics 3, 1988, 279-294.

18. Chou, Ray Y., Robert F. Engle, and Alex Kane, Measuring risk aversion from excess

returns on a stock index, Journal of Econometrics 52, 1992, 201-224.

19. Christie, Andrew A., The stochastic behavior of common stock variances : Value, leverage,

and interest rate effects, Journal of Financial Economics 10, 1982, 407-432.

20. Cochrane, John H. Asset Pricing, Princeton University Press, 2001.

21. Gregory, R. Duffee, Time variation in the covariance between stock returns and con-

sumption growth, The Journal of Finance 60(4), 2005, 1673-1712

22. Engle, Robert F. and V. K. Ng, Measuring and testing the impact of news on volatility,

Journal of Finance 48, 1993, 1749-1777.

23. French, Kenneth R., G. William Schwert, and Robert F. Stambaugh, Expected stock re-

turns and volatility, Journal of Financial Economics 19, 1987, 3-29.

24. Glosten, Lawrence R., Ravi Jagannathan, and David E. Runkle, On the relation between

the expected value and the volatility of the nominal excess return on stocks, Journal

of Finance 48, 1993, 1779-1801.

25. Hamilton, J. D. and R. Susmel, Autoregressive conditional heteroskedasticity and changes

in regime, Journal of Econometrics 64, 1994, 307-333.

26. Hamilton, James D. and Gang Lin, Stock market volatility and the business cycle, Journal

of Applied Econometrics 11, 1994, 573-593.

27. Kim, Sei-Wan and Bong-Soo Lee, Stock returns, asymmetric volatility, risk aversion,

and business cycle : some new evidence, Economic Inquiry 46(2), 2008, 131-148.

28. Li, G, Time-varying risk aversion and asset prices, Journal of Banking and Finance

31(1), 2007, 243-306.

29. Li, G., Aggregate stock market behavior and investors low risk aversion, Journal of

Economic Dynamics and Control 32(7), 2008, 2349-2369.

26 23 2 2009

30. Lundblad, C, The risk return tradeoff in the long run, Journal of Financial Economics

85(1), 2007, 123-169.

31. Mele, A, Asymmetric stock market volatility and the cyclical behavior of expected re-

turns, Journal of Financial Economics 86(2), 2007, 446-478.

32. Merton, Robert C., An intertemporal capital asset pricing model, Econometrica 41, 1973,

867-88.

33. Nelson, D., Conditional heteroskedasticity in asset returns : a new approach, Econometr-

ica 59, 1991, 347-370.

34. Poterba, James M. and Lawrence H. Summers. The Persistence of Volatility and Stock

Market fluctuation, American Economic Review 76, 1986, 1142-1151.

35. Schwert, G. W., Business cycles, financial crisis, and stock volatiliy, Carnegie-Rochester

Conference Series on Public Policy 31, 1989, 83-126.

36. Schwert, G. W., Stock returns and real activity : a century of evidence, Journal of Finance

45, 1990, 1237-1257.

37. Whitelaw, Robert F., Time variations and covariations in the expectation and volatility

of stock market returns, Journal of Finance 49(2), 1994, 515-542.

27

< Abstract >14)

Stock Returns and Its Volatility under Business Cycles Changes :

Using Asymmetric GARCH Model

Sei-Wan Kim*

We study how three interrelated phenomena-excess stock returns

and risk relation, risk aversion, and asymmetric volatility movement-

change over business cycles in Korean stock market. In a single framework

of asymmetric GARCH in mean models, we significantly find that the risk

averseness in Korean stock market is dependent on the business cycle and

it increases before the boom periods start (i.e., precyclical risk aversion).

And also the asymmetric volatility is weakened before the boom periods

start.

In Korean stock market, while there is a general agreement about

the trade-off between risk and expected return for cross-sectional secur-

ities within a given time period, there seems to be no such an agreement

about the relation between risk and return over time. There is an extensive

empirical literature that has tried to establish the existence of such an

intertemporal tradeoff between risk and return for stock market indices.

Unfortunately, the results have been inconclusive. Related to this, recently

it has been debated whether risk aversion is state-dependent and whether

it is pro-cyclical or counter-cyclical.

In this paper, we have explored these issues using an empirical model.

We have employed a representative asymmetric GARCH-M model allowing

for potential business cycle effects to examine a time-varying inter-

temporal relation between excess return and risk using a series of business

cycle dummy variables.

Given our finding of a time-varying risk-return relation over busi-

ness cycles, we have attempted to infer its implication for time-varying

risk aversion over the business cycles.

Our findings can be summarized as follows. First, in the simple

GARCH models without allowing for the business cycle effect, the risk pre-

* Ewha Womans University, Department of Economics, 11-1 Daehyun-Dong, Seodaemun-Gu, Seoul,

Korea(Tel : 02-3277-4467, E-mail : [email protected])

28 23 2 2009

mium coefficient does not show any clear and significant relation between

risk and excess return in Korean stock market over 1995 to 2008 period.

Even though we allow for a business cycle factor (boom and recession),

the risk premium coefficient is still insignificantly changed between the

boom and recession periods. This result is quite consistent over previous

studies about Korean stock market.

However the risk premium coefficient significantly increases in the

3-month before the boom start period. Since the coefficient of volatility

in the excess mean return equation is usually characterized as measuring

the time-varying risk aversion parameter [e.g., Merton (1980)], our finding

suggests increased risk aversion in the 3-month before the boom start

period or a precyclical movement of risk aversion.

Secondly, we find that the asymmetric movement of volatility is also

state-dependent, and the intensity of it changes over business cycles.

Specifically, we find that asymmetric volatility is weakened significantly

in the 3-month before the boom start period.

Our finding of state-dependent and procyclical risk aversion helps

us understand not only the larger risk premium for a given risk in the

3-month before the boom start period but also weakened asymmetric vola-

tility during the 3-month before the boom start period, in particular by

extending Campbell and Hentschels (1992) argument, both of which are

observed based on GARCH-M models with business cycle dummies. Regard-

ing the asymmetric volatility movement, Black (1976) argues that it could

be due to an increase in leverage that occurs when the market value of

a firm declines.

However, we find that investors are strongly risk-averse during the

3-month before the boom start period. As such, investors become more

sensitive to the leverage effect, and the leverage effect hypothesis antici-

pates that asymmetric volatility will get stronger in the 3-month before

the boom start period. This prediction is not easily compatible with our

finding of weakened asymmetric volatility during the 3-month before the

boom start period.

Key words : Stock Return, Asymmetric Volatility, Risk Averseness, Business

Cycle

JEL Classification : C32, E32, G12

/ColorImageDict > /JPEG2000ColorACSImageDict > /JPEG2000ColorImageDict > /AntiAliasGrayImages false /CropGrayImages true /GrayImageMinResolution 300 /GrayImageMinResolutionPolicy /OK /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 300 /GrayImageDepth -1 /GrayImageMinDownsampleDepth 2 /GrayImageDownsampleThreshold 1.50000 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages true /GrayImageAutoFilterStrategy /JPEG /GrayACSImageDict > /GrayImageDict > /JPEG2000GrayACSImageDict > /JPEG2000GrayImageDict > /AntiAliasMonoImages false /CropMonoImages true /MonoImageMinResolution 1200 /MonoImageMinResolutionPolicy /OK /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 1200 /MonoImageDepth -1 /MonoImageDownsampleThreshold 1.50000 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict > /AllowPSXObjects false /CheckCompliance [ /None ] /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly false /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile () /PDFXOutputConditionIdentifier () /PDFXOutputCondition () /PDFXRegistryName () /PDFXTrapped /False

/Description > /Namespace [ (Adobe) (Common) (1.0) ] /OtherNamespaces [ > /FormElements false /GenerateStructure true /IncludeBookmarks false /IncludeHyperlinks false /IncludeInteractive false /IncludeLayers false /IncludeProfiles true /MultimediaHandling /UseObjectSettings /Namespace [ (Adobe) (CreativeSuite) (2.0) ] /PDFXOutputIntentProfileSelector /NA /PreserveEditing true /UntaggedCMYKHandling /LeaveUntagged /UntaggedRGBHandling /LeaveUntagged /UseDocumentBleed false >> ]>> setdistillerparams> setpagedevice