우리나라에서의 디플레이션 발생 위험...

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우리나라에서의 디플레이션 발생 위험 평가 117 우리나라에서의 디플레이션 발생 위험 평가 * 글로벌 금융위기 등으로 2008.7월 이후 미국, 유럽, 일본 등 주요국의 물가상승률이 하 락세로 돌아서고 일부 기관들이 주요국에 대한 향후 인플레이션 전망치를 마이너스대로 발표하면서 디플레이션 발생 가능성에 대한 우려감이 커지고 있다. 일반적으로 디플레 이션은 장기경기침체로 인식되어 디플레이션이라는 용어 자체가 확산될 경우 금융시장 에 큰 영향을 미칠 수 있고 경제주체들의 심리적 불안을 심화시키는 요인으로 작용할 수 있다. 최근 우리나라에서도 올해 경제가 당초 예상보다 더 악화될 우려가 커지고 있는 가운 데 일부에서 디플레이션 발생 가능성을 제기하고 있다. 연평균 기준으로 볼 때 우리나 라에서는 1966년 이후 마이너스 물가상승률(소비자물가기준)을 보인 예는 한 차례도 없 었다. 그러나 앞으로 글로벌 경기침체가 예상보다 깊고 장기적으로 진행될 경우 일부 품목을 중심으로 물가상승이 급속히 둔화될 가능성을 배제하기 어렵다. 이러한 관점에 서 본 연구는 IMF 등에서 제시하고 있는 기준과 계량적 분석을 통해 우리나라에서의 디플레이션 발생 가능성을 구체적인 수치로 시산·평가해 보고자 한다. 2008년말 기준으로 IMF 취약성 지수 및 분포 특징 등 다양한 방법론을 이용하여 최 근 우리나라에서의 디플레이션 발생 위험 정도를 평가해본 결과 그 가능성은 매우 낮은 것으로 판단되었다. 아울러 2009년중 인플레이션 발생에 대한 상하방 위험 확률을 모 두 고려해 보면 아직까지는 상방위험이 더 큰 것으로 분석되었다. JEL Classification Number: C5, E31, E37 핵심 주제어: 디플레이션, 인플레이션, 통화정책 * 한국은행 조사국 통화재정팀 과장(e-mail : [email protected]) 본 논문의 개선을 위해 논평을 해주신 익명의 두 분 심사위원들과 논문 작성과정에 도움을 주신 여 러 분들께 감사드린다. 논문 투고일 : 2009.3.14, 논문 수정일 : 2010.5.23, 게재 확정일 : 2010.6.7.

Transcript of 우리나라에서의 디플레이션 발생 위험...

  • 117

    *

    1)

    2008.7 , ,

    .

    .

    .

    1966 ()

    .

    .

    IMF

    .

    2008 IMF

    . 2009

    .

    JEL Classification Number: C5, E31, E37

    : , ,

    * (e-mail : [email protected])

    .

    : 2009.3.14, : 2010.5.23, : 2010.6.7.

  • 118 16 2 (2010.6)

    .

    2008.7 , ,

    1)

    2)

    . FRB 2008.10 (FOMC)

    3)

    .

    .

    .

    1966 ()

    .

    .

    .

    .

    1) () 2008 7 12 5.5% 0.1%, 4.0% 1.6%, 2.3% 0.4% .

    2) 2009 Global Insight(2.2%), Morgan Stanley(1.3%), Citi(1.2%), Goldman Sachs(0.8%), Barclays(0.7%)

    Citi(1.3%), Goldman Sachs(0.7%), UBS(0.6%), Barclays(0.4%), Global Insight(0.3%) . (0.2%1.1%) .

    3) Some FOMC members thought aggressive easing "should reduce the odds of a deflationary

    outcome" .

  • 119

    .

    .

    .

    4) 2009 0.84.0% .

    2009

    .

    (conditional mean)

    . VaR(Value-

    at-Risk)5)

    .

    IMF

    .

    IMF

    .

    .

    .

    4) 2008 Global Insight(0.8%), Deutsche Bank(1.6%), Goldman Sachs(2.0%), Barclays(2.2%), Merrill Lynch(2.5%), KDI(2.6%) IMFMorgan StanleyCITI (3.0%) 8 .

    5) VaR .

  • 120 16 2 (2010.6)

    . 2008

    IMF 2009

    . 2009

    .

    .

    .

    IMF ,

    ,

    .

    .

    .

    .

    1.

    negative

    . (historical episodes)

    (Bordo and Filado 2005) ( ) (:

    (12%) )

    .

    (temporarily)

    (sustained fall) .

    (sector-specific)

  • 121

    . CPI

    GDP PPI

    .

    .

    .

    (positive) (disinflation) .

    (shift)

    . (benign deflation)

    .

    (malign deflation) ,

    .

    .

    2.

    . ,

    .

    . ,

    .

    . , .

    . ,

    (debt deflation) .

  • 122 16 2 (2010.6)

    ,

    .

    (Fisher 1933)

    (Minsky 1982)

    (Bernanke 1983) . ,

    . (zero

    bound)

    .

    (Ricardian equivalence effect)

    (crowding-out effect) . ,

    (deflationary spiral) . , ()

    ()

    .

    3.

    .

    .

    . (volatility)

    .

    1966 ( )

    (negative ) .

    .

  • 123

    (upward bias)6)

    1% 3 . 3 1973

    (78 0.30.9%), 1987(12 0.50.9%) 1999(29, 0.2

    0.9%).7)

    Changes of CPI in Korea

    Annual Average Changes (%) Year-over-Year Changes (%)

    0

    5

    10

    15

    20

    25

    30

    65 70 75 80 85 90 95 00 05

    0

    5

    10

    15

    20

    25

    30

    35

    65 70 75 80 85 90 95 00 05

    Source: The Statistics Korea

    .

    .

    IMF

    6) (measurement bias) . (new product bias), (quality change bias), (substitution bias), (outlet bias) . , , 1%1.5%p . (measured bias-adjusted basis) .

    7) 1973 , 1987 , 1999 .

  • 124 16 2 (2010.6)

    .

    .

    1. IMF ( )

    2003 IMF8)

    .

    (Index of Deflation Vulnerability)

    .

    .

    , ,

    , 4

    . 4 11

    (threshold)9) 1

    0 .

    .

    8) IMF Task Force Deflation: Determinants, Risks, and Policy Options' .

    9) IMF(Kumar et al. 2003) .

  • 125

    Components of IMF Deflation Vulnerability Index

    Aggregate

    Prices

    - If annual inflation, measured as a change in the CPI, was less than

    0.5%, the value of binary indicator is 1

    - If annual inflation, measured as a change in the Core CPI, was

    less than 0.5%, the value is 1

    - If annual inflation, measured as a change in the GDP deflator, was

    less than 0.5%, the value is 1

    Output gap

    - If the output gap had widened by more than 2 percentage points

    over the past 4 quarters, the value is 1

    - If the current output gap was more than -2%, the value is 1

    - If real GDP growth over the past three years was less than the

    annual average growth over the preceding decade, the value is 1

    Asset

    Markets

    - If the broad measure of the stock market over the past three years

    had fallen by more than 30%, the value is 1

    - If the real effective exchange rate had appreciated by more than

    4% over the past four quarters, the value is 1

    Credit &

    Monetary

    Indicators

    - If private, nominal credit growth was less than nominal GDP

    growth over the past four quarters, the value is 1

    - If cumulative private, nominal credit growth over the past three

    years was less than 10%, the value is 1

    - If broad money (M3) growth on a y/y basis grew slower than

    base money by two percentage points (or less) over the past eight

    quarters, the value is 1

    Note: IMF(2003) defined output gap as

    11 10)

    (High), (Moderate), (Low),

    (Minimal) 4 .

    .

    10) IMF(Kumar et al. 2003) .

  • 126 16 2 (2010.6)

    IMF Deflation Vulnerability Index and Risk Assessment

    Index(x) x

  • 127

    2008.3 4

    (Minimal), 3

    (Moderate) .14)

    Trends of Deflation Vulnerability Index

    (1990:Q1~2008:Q3)

    United States Japan

    .0

    .1

    .2

    .3

    .4

    .5

    .6

    .7

    .8

    -2

    -1

    0

    1

    2

    3

    4

    5

    6

    7

    90 92 94 96 98 00 02 04 06 08

    CPI ( , )

    ( )

    (%)

    .0

    .1

    .2

    .3

    .4

    .5

    .6

    .7

    .8

    -2

    -1

    0

    1

    2

    3

    4

    5

    6

    7

    90 92 94 96 98 00 02 04 06 08

    CPI ( , )

    ( )

    (%)

    14) IMF . . IMF IMF 2003, 2009 (35) IMF . , IMF . IMF (event) , signal-to-noise-ratio , 1 signaling window 24 IMF .

  • 128 16 2 (2010.6)

    2. ( )

    Kilian and Manganelli(2007)

    .

    (bootstrap)

    ,

    .15)

    .

    (1)

    (2)

    , ,

    . (1) (2)

    () ()

    .

    Kilian and Manganelli

    16)

    . Negative

    15) Kilian and Manganelli(2007) Fan chart .

    16) Kilian and Manganelli(2007) , 21%( 3%, 1%) .

  • 129

    .

    (2.5%)

    (upward bias)

    .

    .

    Stock and Watson(2002)

    .

    (3)

    , (information variables) ,

    (principal component analysis) (factor)

    .

    Kilian and Manganelli ,

    ,

    3 17) . Kilian and Manganelli

    ( (3))

    ( 2005) Stock and Watson

    .

    16 18)

    1985.12008.12 .

    Buhlmann and Yu(2003) () ,

    (Information criterion )

    .19) 20072009

    17) 3 i) , ii) , iii) .

    18) , , , , , , , M1, M2, Lf, , , OECD, (), , , , , .

  • 130 16 2 (2010.6)

    30.5%( 3.5%, 2.5%) 21%( 3%, 1%)

    .

    .

    2008 ( 30.5% )

    ( ) (

    ) .

    (21%)

    (1% ) .

    (2008.11 )

    40% 1990

    (2008.10 )

    4 .

    .

    Estimation Results of Deflation and Inflation Risk

    Korea US Japan

    target range 30.5% target range 21%

    Inflation Risk(A) 0.38 0.59 0.26 0.27

    Deflation Risk(B) 0.26 0.01 0.37 1.03

    A+B 0.12 0.58 0.11 0.76

    Inflation forecast(Conditional mean) 3.11 3.11 1.69 0.53

    .

    (198090)

    19) (2008) .

  • 131

    2000 .

    Trends of Estimated Deflation and Inflation Risk in Korea

    (Inflation Target Range 30.5%)

    Average Hystorical Risks by dacade in Korea

    (Inflation Target Range 30.5%)

    1980s 1990s 2000s

    Inflation Risk(A) 1.85 2.07 0.64

    Deflation Risk(B) 0.04 0.05 0.36

    A+B 1.80 2.01 0.29

    .

  • 132 16 2 (2010.6)

    Average Hystorical Risks by dacade in US and Japan

    (Inflation Target Range 21%)

    1960s 1970s 1980s 1990s 2000s

    Inflation Risk(A)

    United States 0.73 2.95 2.86 1.01 0.78

    Japan 3.68 4.62 0.85 0.39 0.16

    Deflation Risk(B)

    United States 0.12 0.00 0.03 0.05 0.08

    Japan 0.00 0.00 0.19 1.06 1.84

    A+B

    United States 0.61 2.95 2.83 0.96 0.70

    Japan 3.68 4.62 0.67 0.67 1.68

    Trends of Estimated Deflation and Inflation Risk

    (Inflation Target Range 21%)

    United States

    Japan

  • 133

    3. ( )

    .

    .

    (Distributional characteristics)

    VaR(Value-at-Risk)

    .

    .

    ( )

    .

    20)

    .

    (price stickiness)

    . Ball and Mankiw(1995) (skewed to right)

    (price shock)

    21) .

    (skewed to left) .

    .

    ()

    20) inflation is always, and everywhere a monetary phenomenon .

    21) 1970 .

  • 134 16 2 (2010.6)

    . Mills(1927)

    (stylized

    fact)22) 23)

    .

    .

    .

    (4)

    ,

    (Dispersion) (Skewness) . (4) Ball and Mankiw

    (1995) .24)

    19752008

    CPI CPI

    (489) . (Outlier

    detection test) (Robust measure)25) .

    22) (Dispersion) (Skewness) .

    23) Ball and Mankiw(1995), Debell and Lamont(1997), Aucremanne et al(2002), Amano and Macklem(1997), Dopke and Pierdzioch(2003), Nishizaki(2000), EU Fielding and Mizen(2000), Florio(2005), Caraballo and Dabus(2005), Assarsson and Riksbank (2003) .

    24) (4) (Dispersion, Skewness, Kurtosis) ( , , Akaike Schwartz) (4) . .

    25) Median absolute distance(MAD), L-moment .

  • 135

    .

    ( ) ( 26), 10%

    ) .27)

    Estimation Results

    Regressor constant SD SK SD*SKMarginal

    Effect(SD)

    Marginal

    Effect(SK)

    coefficient -0.011 0.458 0.692 -0.258 6.988 1.081 0.120

    p-value (0.60) (0.01) (0.14) (0.25) (0.09) (0.01) (0.07)

    Note: , AIC=-3.99, SC=-3.76, RMSE=0.028

    .

    VaR(value-at-risk)

    .

    .

    () i)

    ( 1) ii)

    ( 2) iii) 50% ( 3)

    .28)

  • 136 16 2 (2010.6)

    7> .

    ( 2) 50%

    ( 3) 2009

    .29)

    Inflation Forecast by Scenario of Distributional Characteristic

    AssumptionScenario 1

    Skewness=0.05

    Scenario 2

    Skewness=0.1

    Scenario 3

    Skewness=0.15

    Dispersion=0.03 2.4% 2.2% 2.1%Dispersion=0.05 2.0% 1.5% 1.1%

    Note: Output gap measured by HP filtering of GDP is included in the inflation

    equation to capture the excessive demand pressures.

    .

    IMF

    2008

    . IMF

    .

    .

    .

    2009

    .

    29) (1.1%2.4%) Value-at-Risk (potential extreme loss) .

  • 137

    .30)

    .31)

    (,

    ) .

    FRB 32)

    .

    .

    .

    30) ( 2008) 4 6 . ( 2009) 76.5%( 82.5%) . 2008 . () 2008.12 4.0% 20052007 (3.0%) .

    31) . Atkeson and Kehoe(2004) (19291934) . 16 GDP (19291934) 0.4 . (18202000) ( 0.04 0.08) .

    32) FRB 2008.10 (FOMC) . 2008.10 CPI 1.0% , 1947 FRB . Meltzer(Carnegie Mellon) FRB "go back to school" .

  • 138 16 2 (2010.6)

    .

    ( ,

    ) .

    ()

    ( , )

    ( )

    .

    ( )

    ( )

    .

    Right Skewed Distribution Left Skewed Distribution

    (Inflationary process) (Deflationary process)

    Notes: 1) Right skewed distribution represents SuN distribution with a mean of 0,

    standard deviation of 0.12, skewness of 3, kurtosis of 25 and menu cost of 0.15

    while left skewed distribution represents SuN distribution with a mean of 0,

    standard deviation of 0.12, skewness of -3, kurtosis of 25 and menu cost of 0.15

    2) The computed inflation of right skewed distribution of price changes is +0.022 while

    the computed inflation of left skewed distribution of price changes is -0.022.

    (Skewness) (Dispersion) (kurtosis)

    .

    (shape)

    .

  • 139

    . 33)

    .

    1990

    .

    .

    Korea Japan

    -.10

    -.05

    .00

    .05

    .10

    .15

    .20

    .25

    .30

    1980 1985 1990 1995 2000 2005

    InflationSkewness

    -.01

    .00

    .01

    .02

    .03

    .04

    .05

    .06

    .07

    .08

    -.4

    -.3

    -.2

    -.1

    .0

    .1

    .2

    .3

    .4

    .5

    1980 1985 1990 1995 2000 2005

    Inflation(left)

    Skewness(right)

    33) (Boxplot, Carling method Hampel method ) 914% outlier Classical measure outlier Robust measure(Greenwood(1979) L-moment: 1 +1 ) .

  • 140 16 2 (2010.6)

    (2008), Estimation of Hybrid Phillips Curve in Korea,"319

    (2009), ,15 4

    (2005), ,11

    3

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    Atkeson, Andrew and Patrick Kehoe(2004), Deflation and Depression: Is There an

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    Aucremanne, Luc, Guy Brys, Mia Hubert, Peter J. Rousseeuw, and Anja

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  • 142 16 2 (2010.6)

    Assessment of Deflation Risk in Korea

    Woong Kim

    Due to the global financial crisis, the inflation in major countries such as

    U.S., Europe and Japan is on the decline and some agencies forecast the

    expected inflation in major countries to be in a negative territory. These

    phenomena are exacerbating the concerns about deflation risk. If deflation,

    which is generally perceived as long run economic recession, become widely

    contagious, such deflation could severely affect financial markets and might

    serve as a factor seriously rattling economic entities' confidence about

    market conditions.

    Recently, with the growing concerns that economy would be deteriorated

    more than expected, some are raising the possibility of deflation. On a basis

    of annual average changes, inflation(consumer price basis) has never been

    recorded to be minus since 1966. However, if the global economic downturn

    deepens and persists in a long run, it is difficult to deny the possibility

    that, starting largely in some commodities, inflation would sharply slow

    down. This study strives to assess the risk of deflation in Korea by

    calculating it into concrete figures based on the methodology used by the

    International Monetary Fund, and other econometric analyses.

    On the end of 2008 basis, the risk of deflation in Korea is evaluated by

    using a variety of methodology such as IMF Vulnerability Index and the

    distributional characteristics of price changes. The results show the

    possibility of deflation is extremely slim. Furthermore, according to the

    analysis of both the upside and downside risk probabilities about the

    occurrence of inflation in 2009, former seems greater than the latter.

    JEL Classification Number: C3, E31, E37

    Keywords: Deflation, Inflation, Monetary policy