Inflation Dynamics During the Financial Crisis

Transcription

1 Inflation Dynamics During the Financial Crisis S. Gilchrist 1 R. Schoenle 2 J. W. Sim 3 E. Zakrajšek 3 1 Boston University and NBER 2 Brandeis University 3 Federal Reserve Board Theory and Methods in Macroeconomics Conference Lausanne February 13th, 2014 DISCLAIMER: The views expressed are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Board of Governors of the Federal Reserve System or of anyone else associated with the Federal Reserve System.

2 MOTIVATION In spite of massive contraction in economic activity during the financial crisis, the general level of prices has remained surprisingly stable. What accounts for the absence of deflationary pressures in light of the enormous and persistent resource slack in the economy? This paper investigates the effect of financial conditions on firms price-setting behavior during the Great Recession.

3 FINANCIAL FRICTIONS IN MACROECONOMIC MODELS Financial Accelerator Mechanism Borrowing capacity of firms and households depends on borrower net worth. (Kyotaki & Moore [1997], Bernanke, Gertler and Gilchrist [1999], Christiano, Motto and Rostagno [2013]) Shocks to economy are amplified by endogenous movement in asset prices. Positive comovement between inflation and output.

4 FINANCIAL FRICTIONS IN MACROECONOMIC MODELS Reallocation Mechanism Financial frictions distort allocation of inputs across production units. (Kyotaki [1998], Basetto, Cagetti & DeNardi [2010], Buera & Moll [2012]) Shocks to the economy create endogenous movements in aggregate TFP. Negative comovement between inflation and output?

5 FINANCIAL FRICTIONS IN MACROECONOMIC MODELS Pricing Mechanism Financial frictions distort pricing decision in customer markets framework. (Gottfries [1991],Chevalier & Scharfstein [1996], Barth & Ramey [2001]) Shocks to the economy create endogenous movements in markups. Negative comovement between inflation and output.

6 OVERVIEW Merge item-level prices of individual producers included in the Producers Price Index (PPI) to their income and balance sheet data from Compustat. Analyze how balance sheet conditions influence firm-level price-setting behavior. Study inflation and output dynamics in a DSGE model that embeds financial frictions in a customer-markets framework.

7 DATA SOURCES Monthly good-level price data underlying the PPI. (Nakamura & Steinsson [2008]; Goldberg & Hellerstein [2009]; Bhattarai & Schoenle [2010]) Match 700+ PPI respondents to their income and balance sheet data from Compustat. Sample period: Jan2005 Sep2012

8 AGGREGATE INFLATION All PPI respondents vs. publicly-traded firms 3-month moving average Percent Full sample Matched sample NOTE: Seasonally-adjusted weighted average inflation at a monthly rate.

9 RELATIVE INFLATION BY FIRM CHARACTERISTICS Sort firms above/below median value based on observable characteristics in periods t 1... t 4. Financial characteristics: Liquidity: (Cash[t] + LiquidAssets[t])/TotalAssets[t] Cashflow: OperatingIncome[t]/TotalAssets[t-1] Interest coverage: InterestExpense[t]/Sales[t] Other characteristics: Customer markets vs. operating efficiency: SGAX[t]/Sales[t] Durability of output: durable vs. nondurable goods

10 RELATIVE INFLATION Financially unconstrained firms 3-month moving average Percent High liquid assets High operating income Low interest expense NOTE: Weighted average monthly inflation relative to industry (2-digit NAICS) inflation.

11 RELATIVE INFLATION Financially constrained firms 3-month moving average Percent 3 Low liquid assets Low operating income High interest expense NOTE: Weighted average monthly inflation relative to industry (2-digit NAICS) inflation.

12 RELATIVE INFLATION Effect of Financial Frictions, Cumulated Response Monthly Cumulative Percent Low liquid assets High liquid assets Low operating income High operating income High interest expense Low interest expense NOTE: Cumulated weighted average monthly inflation relative to industry (2-digit NAICS) inflation.

13 RELATIVE INFLATION By durability of output and financial condition 3-month moving average Percent High liquid assets - durable goods Low liquid assets - durable goods High liquid assets - nondurable goods Low liquid assets - nondurable goods NOTE: Weighted average monthly inflation relative to industry (2-digit NAICS) inflation.

14 PRICE ADJUSTMENT AND FIRM CHARACTERISTICS Multinomial logit specification: + Pr( p ij,t+1 ) = 0 (base) = Λ(X jt ; β t ) X jt = liquidity ratio and other controls Includes fixed industry (3-digit NAICS) effects. Estimated using four-quarter rolling window.

15 PRICE CHANGE ELASTICITIES With respect to liquidity ratio Downward Price Changes Upward Price Changes Elasticity 0.4 Elasticity Estimate 95% Confidence interval

16 ELASTICITIES OF PRICE CHANGES With Respect to SGAX Downward Price Changes Upward Price Changes Elasticity 0.2 Elasticity

17 PRICE ADJUSTMENT AND FIRM CHARACTERISTICS Price change regression: p i,j,t+1 = α j + βx j,t + ɛ i,j,t X j,t = liquidity ratio and other controls. Includes firm-level fixed effects: controls for many aspects of firm heterogeneity such as productivity. Estimated using four-quarter rolling window.

18 PRICE CHANGE COEFFICIENTS All Price Changes Estimated coefficient Coefficient NOTE: Estimated Coefficients on Liquidity Ratio.

19 GE Model Customer markets imply firms trade off current profits for future market share. Financial frictions imply firms discount the future more when demand is low therefore keep mark-up high. Embed this into GE model with nominal price rigidities.

20 PREFERENCES: DEEP HABITS Ravn, Schmitt-Grohe and Uribe [2006] Maximization max E t s=0 [ 1 ( Aggregator: x j t 0 Law of motion: δ t = demand shock β s U(x j t+s δ t+s, h j t+s ); j [0, 1] c j it s θ it 1 ) 1 1/η di] 1/(1 1/η) s it = ρs i,t 1 + (1 ρ)c it ; 0 < ρ < 1

21 TECHNOLOGY Production function (labor input, fixed operating costs): [ ] α At y it = h it φ i ; 0 < α 1 a it A t = persistent aggregate technology shock a it = i.i.d. idiosyncratic technology shock with log a it N( 0.5σ 2, σ 2 )

22 FINANCIAL FRICTIONS Firms make production decisions prior to realization of marginal cost. If realized operating income is negative, firms must raise costly equity finance: ϕ (0, 1) = constant per-unit dilution costs of new equity Implications: A low mark-up is an aggressive, but risky investment. Exposes the firm to the risk of operating losses, which must be covered by external financing.

23 Nominal rigidities and monetary policy: Price adjustment: (Rotemberg [1982]) ( ) γ 2 Pit π c t = γ ( 2 P i,t 1 2 Taylor rule: [ ( πt ) ρπ r t = max {0, (1 + r t 1 ) ρr (1 + r) π π t ) p 2 it π c t ; p it P it p i,t 1 ( yt y t P t ) ρy ] 1 ρr 1}

24 FIRM PROBLEM Maximize the expected present value of dividends: { [( ) α At L = E 0 m 0,t d it + κ it h it φ k c it] a t=0 it [ + ξ it p it c it w t h it γ ( ) 2 p it π t π c t ϕ(d it)] 2 p i,t 1 [ (pit ) ] } η + ν it s θ(1 η) i,t 1 p x t c it + λ it [ρs i,t 1 + (1 ρ)c it s it ] t Externality-adjusted composite price index: [ ] 1 1/(1 η) p t 0 (p its θ i,t 1 )1 η di p it, c it, s it chosen before the realization of idiosyncratic shock a it. d it, h it chosen after the realization of idiosyncratic shock a it.

25 Equity issuance The FOC for d it : ξ(a it ) = { 1 if ait a E t 1/(1 ϕ) if a it > a E t where a E t is the idiosyncratic productivity level when dividends are exactly zero: a E t = c t (c t + φ) 1/α A t w t [ 1 γ 2 (π t π) 2]

26 The shadow value of internal funds The expected cost of external funds is: E a t [ξ it ] = Φ(z E t ) ϕ [1 Φ(zE t )] = 1 + ϕ 1 ϕ [1 Φ(zE t )] 1 where z E t = σ 1 (log a E t + 0.5σ 2 ).

27 Price-setting without nominal rigidities No customer markets: 1 = With customer markets: [ ] µt 1 1 = η µ t [ + ψe t s=t ( η ) 1 η 1 µ t β ts E a s+1 [ξ i,s+1] E a t [ξ it] [ ] ] µs+1 1 µ s+1

28 LOG-LINEARIZED PHILLIPS CURVE [ ω(η 1) ] ˆπ t = ˆµ t + E t χ δ s t+1 ˆµ s+1 + βe t [ˆπ t+1 ] γ s=t [ ] + 1 γ [η ω(η 1)] E t χ δ s t+1 (ˆξ t ˆξ s+1 ) ˆβ t,s+1 s=t ˆµ t = (marginal) mark-up ˆξ t = shadow value of internal funds ˆβ t,s+1 = capitalized growth of customer base

29 Calibration Preferences and production Constant relative risk aversion, γ x 1.00 Deep habit, θ 0.95 Persistence of deep habit, ρ 0.95 Elasticity of labor supply, 1/γ h 5.00 Elasticity of substitution, η 2.00 Returns to scale, α 0.80 Fixed operation cost, φ 0.21 Nominal rigidity and monetary policy Price adjustment cost, γ p 1 Wage adjustment cost, γ w 3 Monetary policy inertia, ρ r 0.75 Taylor rule coefficient for inflation gap, ρ π 1.50 Financial Frictions Equity issuance cost, ϕ 0.30, 0.50 Idiosyncratic volatility (a.r.), σ 0.20

30 DEMAND SHOCK: FINANCIAL CRISIS (ϕ = 0.5) (a) Output % (b) Value of intnl. funds pps (c) Mark-up pps (d) Inflation pps w/o financial frictions w/ financial frictions

31 DEMAND SHOCK With temporary increase in financial frictions (a) Output % 0.5 (b) Value of intnl. funds pps. 6.0 (c) Mark-up pps. 1.2 (d) Inflation pps w/ fixed dilution costs w/ time-varying dilution costs Fixed dilution cost: ϕ = 0.5 Temporary increase: ϕ =

32 DEMAND SHOCK Policy dilemma in the presence of financial frictions (a) Mark-up pps. 0.4 (b) Inflation pps. 0.6 (c) Output % 0.3 (d) Real interest rate pps Taylor rule output gap coefficients: blue = 0; red = 0.125; green = 0.250

33 HETEROGENEOUS FIRMS Sectors differ by operating efficiency: 0 φ 1 < φ 2 Fixed measures of firms ω 1 = ω 2 = 1 2 Equilibrium dispersion of relative prices: π t = [ 2 k=1 ω k p 1 η k,t 1 π1 η kt ] 1/(1 η) ; π kt P kt p kt P kt /P t = sector-specific relative price P k,t 1

34 PRICE WAR IN RESPONSE TO FINANCIAL SHOCKS Heterogeneous firms (a) Relative prices (b) Output % % Financially strong Financially weak Financially weak -1.0 Financially strong Case I: φ 1 = 0.8 φ, φ 2 = φ and ω 1 = ω 2 = 0.5 Case II: φ 1 = 0, φ 2 = φ and ω 1 = ω 2 = 0.5

35 PRICE WAR IN RESPONSE TO FINANCIAL SHOCKS Heterogeneous firms (a) Relative prices (b) Output % % Financially strong Financially weak Financially weak -1.0 Financially strong Aggregate Aggregate Case I: φ 1 = 0.8 φ, φ 2 = φ and ω 1 = ω 2 = 0.5 Case II: φ 1 = 0, φ 2 = φ and ω 1 = ω 2 = 0.5

36 PRICE WAR IN RESPONSE TO FINANCIAL SHOCKS Heterogeneous firms (a) Relative prices (b) Output % % Financially strong Financially weak Financially weak Financially strong Aggregate Aggregate Case I: φ 1 = 0.8 φ, φ 2 = φ and ω 1 = ω 2 = 0.5 Case II: φ 1 = 0, φ 2 = φ and ω 1 = ω 2 = 0.5

37 PRICE WAR IN RESPONSE TO FINANCIAL SHOCKS Heterogeneous firms (a) Relative prices (b) Output % % Financially strong Financially weak Financially weak Financially strong Aggregate Aggregate Aggregate Aggregate Case I: φ 1 = 0.8 φ, φ 2 = φ and ω 1 = ω 2 = 0.5 Case II: φ 1 = 0, φ 2 = φ and ω 1 = ω 2 = 0.5

38 CONCLUSION Balance sheet conditions played an important role in price-setting dynamics during the financial crisis: Financially healthy firms decreased prices, while financially weak firms increased prices. DSGE model customer markets and financial frictions implies Attenuation of inflation dynamics in response to demand shocks. Severe contraction in response to temporary financial shocks. Paradox of financial strength with heterogenous firms. Monetary policy: inflation-output tradeoff in response to demand or financial shocks.