A dynamic theory of sovereign debt and structural reforms with three interacting frictions: limited enforcement, limited commitment, and incomplete markets.
A dynamic theory of sovereign debt and structural reforms with three interacting frictions: limited enforcement, limited commitment, and incomplete markets.
Fiat value in the theory of value, by Edward C Prescott (Arizona State Univer...ADEMU_Project
Technology is rapidly advancing in the information processing area, which is changing the monetary/payment system. It's now technically feasible to have a currency–less monetary system; Professor Prescott explores such a system.
Non-tradable Goods, Factor Markets Frictions, and International Capital FlowsGRAPE
International capital flows - data vs. theory
1 Feldstein-Horioka puzzle
• corr (S, I ) > 0 in the data
2 Lucas puzzle
• K has not flown to poor countries, despite
K
Y
poor
<
K
Y
rich
3 Allocation Puzzle
• corr (ΔTFP, Δexternal debt) < 0
4 Quantity Puzzle (not as famous as the other three)
• Neo-classical 1-sector model over-predicts international
capital flows by a factor of 10
• Gourinchas and Jeanne (REStud, 2013); Rothert (EL, 2016)
Fiat value in the theory of value, by Edward C Prescott (Arizona State Univer...ADEMU_Project
Technology is rapidly advancing in the information processing area, which is changing the monetary/payment system. It's now technically feasible to have a currency–less monetary system; Professor Prescott explores such a system.
Non-tradable Goods, Factor Markets Frictions, and International Capital FlowsGRAPE
International capital flows - data vs. theory
1 Feldstein-Horioka puzzle
• corr (S, I ) > 0 in the data
2 Lucas puzzle
• K has not flown to poor countries, despite
K
Y
poor
<
K
Y
rich
3 Allocation Puzzle
• corr (ΔTFP, Δexternal debt) < 0
4 Quantity Puzzle (not as famous as the other three)
• Neo-classical 1-sector model over-predicts international
capital flows by a factor of 10
• Gourinchas and Jeanne (REStud, 2013); Rothert (EL, 2016)
Non-tradable Goods, Factor Markets Frictions, and International Capital FlowsGRAPE
International capital flows - data vs. theory
1 Feldstein-Horioka puzzle
• corr (S, I ) > 0 in the data
2 Lucas puzzle
• K has not flown to poor countries, despite
K
Y
poor
<
K
Y
rich
3 Allocation Puzzle
• corr (ΔTFP, Δexternal debt) < 0
4 Quantity Puzzle (not as famous as the other three)
• Neo-classical 1-sector model over-predicts international
capital flows by a factor of 10
• Gourinchas and Jeanne (REStud, 2013); Rothert (EL, 2016)
Agents gradually learn the structure of the economy.
Learning model delivers a sizeable recession in 2008-2010,
...whereas RE model predicts a counterfactual expansion.
In a medium scale model learning still matters.
Relationship between growth, financial development and income inequality.
- Is there nonlinearity in the relationship?
- What are the factors that affect the degree of impact of financial development on income inequality?
Are incentivized old-age savings schemes effective under incomplete rationality?GRAPE
Financing consumption of the elderly in the face of the projected increase in life expectancy is a key challenge for economic policy. Moreover, standard structural models with fully rational agents suggest that about 50-60 percent of old-age consumption is financed with voluntary savings, even in the presence of a fairly generous public pension system. This is clearly inconsistent with either the data, or the alarming simulations of old-age poverty in the years to come. Old-age saving (OAS) schemes are widely used policy instruments to address this challenge, but structural evaluations of such instruments remain rare. We develop a framework with incompletely rational agents: lacking financial literacy and experiencing commitment difficulties. We study a broad selection of OAS schemes and find that they raise welfare of financially illiterate agents and to a lesser extent improve welfare of agents with a high degree of time inconsistency. They also reduce the incidence of poverty at old age. Unfortunately, these instruments are fiscally costly, induce considerable crowd-out and direct fiscal transfers mostly to those agents, who need it the least.
Estimating Financial Frictions under LearningGRAPE
The paper studies the implication of initial beliefs and associated confidence under adaptive learning. We first illustrate how prior beliefs determine learning dynamics and the evolution of endogenous variables in a small DSGE model with credit-constrained agents, in which rational expectations are replaced by constant-gain adaptive learning. We then examine how discretionary experimenting with new macroeconomic policies is affected by expectations that agents have in relation to these policies. More specifically, we show that a newly introduced macro-prudential policy that aims at making leverage counter-cyclical can lead to substantial increase in fluctuations under learning, when the economy is hit by financial shocks, if beliefs reflect imperfect information about the policy experiment.
Trading Strategies Based on Market Impact of Macroeconomic Announcementsby A...Quantopian
We examine returns of several US equity ETFs on the days of major US macroeconomic announcements and compare performance of the buy-and-hold strategy (B&H) with three different strategies that realize daily returns on the announcement days. We show that these strategies may outperform B&H.
Ademu at the European Parliament, 27 March 2018ADEMU_Project
ADEMU scientific co-ordinator Ramon Marimon joined Marco Buti, director general of DG-ECFIN, DG Economic and Financial Affairs, Roberto Gualtieri, MEP and chair of the Committee on Economic and Monetary Affairs at the European Parliament, Maria Kayamanidou, deputy head of DG Research and Innovation at the EC, and Vincenzo Grassi, secretary general of the European University Institute, to discuss ADEMU's proposals for the European Unemployment Insurance System (EUIS) and the European Stability Fund (ESF).
Yes of course, you can easily start mining pi network coin today and sell to legit pi vendors in the United States.
Here the what'sapp contact of my personal vendor.
+12349014282
#pi network #pi coins #legit #passive income
#US
Lecture slide titled Fraud Risk Mitigation, Webinar Lecture Delivered at the Society for West African Internal Audit Practitioners (SWAIAP) on Wednesday, November 8, 2023.
Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
What price will pi network be listed on exchangesDOT TECH
The rate at which pi will be listed is practically unknown. But due to speculations surrounding it the predicted rate is tends to be from 30$ — 50$.
So if you are interested in selling your pi network coins at a high rate tho. Or you can't wait till the mainnet launch in 2026. You can easily trade your pi coins with a merchant.
A merchant is someone who buys pi coins from miners and resell them to Investors looking forward to hold massive quantities till mainnet launch.
I will leave the what's app number of my personal pi vendor to trade with.
+12349014282
when will pi network coin be available on crypto exchange.DOT TECH
There is no set date for when Pi coins will enter the market.
However, the developers are working hard to get them released as soon as possible.
Once they are available, users will be able to exchange other cryptocurrencies for Pi coins on designated exchanges.
But for now the only way to sell your pi coins is through verified pi vendor.
Here is the what'sapp contact of my personal pi vendor
+12349014282
BONKMILLON Unleashes Its Bonkers Potential on Solana.pdfcoingabbar
Introducing BONKMILLON - The Most Bonkers Meme Coin Yet
Let's be real for a second – the world of meme coins can feel like a bit of a circus at times. Every other day, there's a new token promising to take you "to the moon" or offering some groundbreaking utility that'll change the game forever. But how many of them actually deliver on that hype?
This presentation poster infographic delves into the multifaceted impacts of globalization through the lens of Nike, a prominent global brand. It explores how globalization has reshaped Nike's supply chain, marketing strategies, and cultural influence worldwide, examining both the benefits and challenges associated with its global expansion.
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Synthetic Leather Nike
Cotton in Nike Apparel
Nike Shops Worldwide
Nike Manufacturing Countries
Cold Cement Assembly Nike
3D Printing Nike Shoes
Nike Product Development
Nike Marketing Strategies
Nike Customer Feedback
Nike Distribution Centers
Automation in Nike Manufacturing
Nike Consumer Direct Acceleration
Nike Logistics and Transport
Eco-Innovations and Firm Heterogeneity.Evidence from Italian Family and Nonf...
Financial Heterogeneity and Monetary Union
1. Financial Heterogeneity and Monetary Union
S. Gilchrist1 R. Schoenle2 J. Sim3 E. Zakrajˇsek3
1
Boston University and NBER
2
Brandeis University
3
Federal Reserve Board
Barcelona GSE, ADEMU
June 8, 2017
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. INTRODUCTION
Eurozone Crisis (2008–2013)
Classic balance-of-payment crisis:
◮ The mix of overvalued RERs and cheap credit fueled by economic optimism
led to over- and mal-investment
◮ With the Global Financial Crisis came a sudden stop
Resolution of the crisis:
◮ Realignment of overvalued RERs
◮ The mix of deflation in the “periphery” and reflation in the “core”
◮ Surprisingly hard to achieve—why?
3. INTRODUCTION LESSONS FROM THE U.S. EXPERIENCE
“Missing Deflation” in the U.S.
New empirical evidence on the firms’s price-setting behavior during the
2007–09 crisis:
(Gilchrist & Zakrajˇsek [2016]; Gilchrist, Schoenle, Sim & Zakrajˇsek [2017])
◮ Firms with strong balance sheets cut prices
◮ Firms with weak balance sheets raised prices
Similar patterns documented for the euro area
(Montero & Urtasun [2014]; Antoun de Almeida [2015])
Theory:
◮ GSSZ develop a DSGE model that can replicate such price and output
patterns in periods of financial distress
◮ Emphasizes the interaction between financial market frictions and firms’
pricing decisions in customer markets
(Bils [1989]; Chevalier & Scharfstein [1996])
4. INTRODUCTION LESSONS FROM THE U.S. EXPERIENCE
U.S. PPI Inflation
Liquidity constrained vs. unconstrained firms
2005 2006 2007 2008 2009 2010 2011 2012
-25
-20
-15
-10
-5
0
5
10
Percentage points
Low liquidity firms
High liquidity firms
3-month moving average, annualized
NOTE: Weighted average monthly inflation relative to industry (2-digit NAICS) PPI inflation.
SOURCE: Gilchrist, Schoenle, Sim & Zakrajˇsek [2017]
5. INTRODUCTION LESSONS FROM THE U.S. EXPERIENCE
Key Takeaways
Internal liquidity positions played an important role in shaping U.S. firms’
price-setting behavior during the financial crisis.
Disruption in financial markets in 2008 forced firms with limited financial
capacity to significantly increase their prices, whereas their unconstrained
counterparts cut prices during the concomitant economic downturn.
Industry-level data suggests this is a more general phenomenon in
response to financial market disruptions.
6. INTRODUCTION EVIDENCE FROM THE EURO AREA
Euro Area Inflation and Economic Activity
1992–2007 2008–2013
Average (%) Core GIIPS Core GIIPS
Inflation 1.74 4.02 1.49 0.55
Output gap −0.07 0.81 −0.73 −2.98
Unemployment gap 0.46 −0.60 −0.09 1.27
Core = AUT, DEU, BEL, FIN, FRA, NLD; GIIPS = GRC, IRL, ITA, ESP, PRT
SOURCE: AMECO database.
Is lack of disinflationary pressures in the periphery during the crisis
related to financial strains?
7. INTRODUCTION EVIDENCE FROM THE EURO AREA
Financial Conditions and Inflation Dynamics
Panel-versions of the price and wage Phillips Curves:
◮ Prices: accelerationist
πit = αi + βπi,t−1 + λ(uit − ¯uit ) + φ∆VATit + ψ1[i ∈ e] + ǫit ;
◮ Prices: hybrid New Keynesian
πit = αi + βf Et πi,t+1 + βbπi,t−1 + λmcit + φ∆VATit + ψ1[i ∈ e] + ǫit ,
◮ Wages: accelerationist
∆wit = αi + βπi,t−1 + λ(uit − ¯uit ) + φ∆˜zit + ψ1[i ∈ e] + ǫit ;
Data
◮ Countries: AUT, DEU, BEL, FIN, FRA, NLD, GRC, IRL, ITA, ESP, PRT
◮ Estimation period: 1970–2007
Are the PC prediction errors during the crisis related to the degree of
financial strains across countries?
9. INTRODUCTION EVIDENCE FROM THE EURO AREA
Financial Conditions in the Euro Area
Sovereign (5-year) CDS spreads
2008 2010 2012 2014
Percentage points (log scale)
Italy
Greece
Portugal
Spain
Ireland
Mar./Oct.
Periphery countries
0
0.5
2
10
50
200
2008 2010 2012 2014
Percentage points (log scale)
Austria
Belgium
France
Germany
Netherlands
Finland
Mar./Oct.
Core countries
0
0.1
0.5
1
2
4
SOURCE: Markit.
10. INTRODUCTION EVIDENCE FROM THE EURO AREA
Sovereign Distress and Business Credit Conditions
Euro area, 2008–2013
Explanatory Variables (1) (2)
ln CDSi,t−1 0.568 0.832
[0.406, 0.731] [0.493, 1.180]
Adj. R2
0.200 0.210
Time fixed effects N Y
NOTE: Bootstrapped 95% confidence intervals in brackets.
11. INTRODUCTION EVIDENCE FROM THE EURO AREA
Financial Conditions and PC Prediction Errors
Without time fixed effects, 2008–2013
Explanatory Variable
Specification ln CDSi,t−1 ln CDSi,t−1 × 1[i ∈ P] R2
(1) Prices (homogeneous) 0.043 0.601 0.198
[−0.139, 0.227] [0.218, 0.985]
(2) Prices (heterogeneous) 0.204 0.593 0.258
[0.028, 0.372] [0.156, 1.030]
(3) Hybrid NK 0.028 0.299 0.110
[−0.100, 0.156] [0.022, 0.577]
(4) Wages (homogeneous) −0.008 −0.776 0.254
[−0.266, 0.251] [−1.425, 0.100]
(5) Wages (heterogeneous) 0.085 −2.075 0.425
[−0.190, 0.360] [−3.082, −1.069]
NOTE: Bootstrapped 95% confidence intervals in brackets.
12. INTRODUCTION EVIDENCE FROM THE EURO AREA
Financial Conditions and PC Prediction Errors
With time fixed effects, 2008–2013
Explanatory Variable
Specification ln CDSi,t−1 ln CDSi,t−1 × 1[i ∈ P] R2
(1) Prices (homogeneous) 0.044 0.453 0.329
[−0.239, 0.327] [0.092, 0.814]
(2) Prices (heterogeneous) 0.684 0.275 0.419
[0.369, 0.999] [0.031, 0.519]
(3) Hybrid NK 0.125 0.200 0.205
[−0.051, 0.301] [−0.031, 0.410]
(4) Wages (homogeneous) −1.364 −0.495 0.352
[−2.221, −0.506] [−1.359, 0.369]
(5) Wages (heterogeneous) −2.196 −1.469 0.542
[−2.731, −1.661] [−2.550, −0.389]
NOTE: Bootstrapped 95% confidence intervals in brackets.
13. INTRODUCTION EVIDENCE FROM THE EURO AREA
Economic Significance of Financial Factors
Euro area periphery, 2008–2013
2008 2009 2010 2011 2012 2013
-16
-8
0
8
16
Percentage points
Actual price inflation
Effect of financial conditions
Actual wage inflation
Effect of financial conditions
Price and wage inflation
Annual
2008 2009 2010 2011 2012 2013
-28
-14
0
14
28
Percent
Prices
Wages
Counterfactual prices and wages
Annual
NOTE: In deviations from 2008 levels.
14. INTRODUCTION EVIDENCE FROM THE EURO AREA
Price Markups
Euro area, 2000–2015
-10
-5
0
5
10
15
20
25
Percent
Annual
Periphery countries
2000 2005 2010 2015
-10
-5
0
5
10
15
20
25
Percent
Annual
Core countries
2000 2005 2010 2015
NOTE: The markup is equal to minus (100 times) the log or real unit labor costs (2008 = 1).
SOURCE: AMECO database.
15. INTRODUCTION EVIDENCE FROM THE EURO AREA
Financial Conditions and Price Markups
Euro area, 2008–2013
Explanatory Variable
Specification ln CDSi,t−1 ln CDSi,t−1 × 1[i ∈ P] R2
A. Aggregate
(1) Without time fixed effects −0.205 1.378 0.256
[−0.944, 0.534] [0.557, 2.220]
(2) With time fixed effects −0.312 1.148 0.681
[−0.528, −0.095] [0.926, 1.372]
B. Sectoral
(3) Without time fixed effects −0.442 2.556 0.057
[−2.135, 1.252] [0.913, 4.198]
(4) With time fixed effects −0.331 1.974 0.152
[−1.915, 1.254] [1.244, 2.704]
NOTE: Bootstrapped 95% confidence intervals in brackets.
16. MODEL INTRODUCTION
Financial Heterogeneity as a Propagation Mechanism
This paper:
◮ Extend GSSZ [2015] to a two-country setting (“core” and “periphery”)
◮ Study the consequences of forming a monetary union among countries with
heterogeneous financial capacities
Implications:
◮ During a financial crisis in the periphery, core has an incentive to lower
prices to gain market share at home and abroad
◮ Firms in the periphery are forced to raise prices to maintain current
cashflows, thereby sacrificing future market shares
◮ RER appreciating for periphery rather than for core creates a feedback loop
that reinforces liquidity crisis in the periphery
17. MODEL INTRODUCTION
Policy Options
Fiscal Union:
◮ Trading state-contingent bonds among heterogeneous countries
◮ Highly beneficial to the periphery but requires large transfers from the core
Fiscal Devaluation:
◮ Certain mixes of fiscal instruments replicate the devaluation
◮ When can a unilateral fiscal devaluation by the periphery be beneficial to the
core?
18. MODEL ENVIRONMENT
Preferences
Two countries: home (h = periphery) and foreign (f = core)
Continuum of households in each country: j ∈ Nc ≡ [0, 1]
Two types of goods:
home goods (h): c
j
i,h,t , i ∈ Nh ≡ [0, 1]
foreign goods (f ): c
j
i,f,t , i ∈ Nf ≡ [1, 2]
Preferences of household j in the home country:
Et
∞
∑
s=0
δs
U(x
j
t+s, h
j
t+s)
◮ labor (h) is immobile
19. MODEL ENVIRONMENT
“Deep Habits”
Ravn, Schmitt-Grohe & Uribe [2006]
Consumption/habit aggregator:
x
j
t = ∑
k=h,f
Ξk
Nk
c
j
i,k,t /sθ
i,k,t−1
1−1/η
di
1−1/ǫ
1−1/η
1/(1−1/ǫ)
◮ η > 0 is the elasticity of substitution within a type of goods
◮ ǫ > 0 is the elasticity of substitution between the two types of goods
◮ 0 < Ξk < 1 governs the degree of home bias in consumption
◮ si,k,t = good-specific stock of habit
◮ θ < 0 governs the strength of “deep” habits
Law of motion for (external) deep habits:
si,k,t = ρsi,k,t−1 + (1 − ρ)
1
0
c
j
i,k,t dj; k = h, f
◮ “Keeping up with the Joneses” at the good level
20. MODEL ENVIRONMENT
Technology
Continuum of monopolistically competitive firms producing variety of
differentiated goods of type h and type f.
◮ Labor is the only input
Production function of home country firms:
yit = ci,h,t + c∗
i,h,t =
At
ait
hit
α
− φ; i ∈ Nh (0 < α ≤ 1)
◮ At = persistent aggregate technology shock
◮ ait = i.i.d. idiosyncratic cost shock w/ log ait ∼ N(−0.5σ2, σ2)
◮ φ = fixed costs ⇒ firms can incur operating losses
◮ Homogeneous operating costs: φ = φ∗
21. MODEL FRICTIONS
Liquidity Risk
First half of period t:
◮ Collect information about the aggregate state of the economy
◮ Post prices, take orders from customers, and plan production based on
expected marginal cost
Second half of period t:
◮ Idiosyncratic uncertainty is resolved, and firms realize actual marginal cost
◮ Hire labor to fulfill agreed-upon orders and produce output
End of period t:
◮ Pay out all operating profits as dividends
◮ In the case of operating losses, the firm must issue new shares
22. MODEL FRICTIONS
Financial Frictions
Costly external equity financing:
(Myers & Majluf [1984]; Gomes [2001]; Stein [2003])
◮ New shares sold at a discount because of asymmetric information
◮ 1 e claim raises only (1 − ϕ) e of funds (0 < ϕ < 1)
Heterogeneity in financial capacity: ϕ∗ < ϕ
No cross-border ownership of firms.
(Obstfeld & Rogoff [2000])
23. MODEL FRICTIONS
“Beggar Thy Neighbor” at the Micro Level
Deep habits make investment in market share profitable:
◮ Investment takes the form of low markups, which exposes firms to liquidity
risk
◮ Optimal pricing strategy strikes the right balance
Price war:
◮ Liquidity crisis in the periphery is a good time for firms from the core to steal
market share by undercutting their competitors’ prices
“Mr. Marchionne and other auto executives accuse Volkswagen of
exploiting the crisis to gain market share by offering aggressive
discounts. “It’s a bloodbath of pricing and it’s a bloodbath on
margins,” he said.”
– The New York Times, July 25, 2012
24. MODEL FRICTIONS
“Beggar Thy Neighbor” at the Micro Level
Deep habits make investment in market share profitable:
◮ Investment takes the form of low markups, which exposes firms to liquidity
risk
◮ Optimal pricing strategy strikes the right balance
Price war:
◮ Liquidity crisis in the periphery is a good time for firms from the core to steal
market share by undercutting their competitors’ prices
“Mr. Marchionne and other auto executives accuse Volkswagen of
exploiting the crisis to gain market share by offering aggressive
discounts. “It’s a bloodbath of pricing and it’s a bloodbath on
margins,” he said.”
– The New York Times, July 25, 2012
25. MODEL FRICTIONS
Nominal Rigidities
Quadratic costs of adjusting nominal prices:
(Rotemberg [1982]; Erceg, Henderson & Levin [2000])
γp
2
Pi,h,t
Pi,h,t−1
− 1
2
ct +
γ∗
p
2
Qt P∗
t
Pt
P∗
i,h,t
P∗
i,h,t−1
− 1
2
c∗
t ; (γp, γ∗
p > 0)
◮ Qt = nominal exchange rate (home/foreign currency)
◮ Consumer price index (CPI) in the home country:
Pt ≡ ∑
k=h,f
Ξk P1−ε
k,t
1
1−ε
, where Pk,t ≡
Nk
Pi,k,t
1−η
di
1
1−η
; k = h, f
Pricing to market: law of one price does not apply
(Fabiani, Loupias, Martins & Sabbatini [2007])
27. MODEL FRICTIONS
Optimal Pricing
Assume flexible prices and no customer markets.
When α = 1, optimal pricing (home market) ⇒
pi,h,t ph,t =
η
η − 1
accounting markup
×
EA
t [ξit ait ]
EA
t [ξit ]
economic markup
×
Wt /Pt
At
real marginal cost
Financial frictions ⇒
EA
t [ξit ] > 1
EA
t [ξit ait ]
EA
t [ξit ]
= 1 + Cov[ξit ait ] ≥ 1
28. MODEL FRICTIONS
Optimal Pricing (cont.)
Bring back customer markets (still flexible prices!)
Growth-adjusted, compounded discount rate:
˜βt,s ≡ ms,s+1
sh,s+1/sh,s − ρ
1 − ρ
×
s−t
∏
j=1
ρ + χ
sh,t+j /sh,t+j−1 − ρ
1 − ρ
mt+j−1,t+j
Optimal pricing ⇒
pi,h,t ph,t =
η
η − 1
EA
t [ξit ait ]
EA
t [ξit ]
Wt /Pt
At
−
χ
η − 1
Et
∞
∑
s=t+1
˜βt,s
EA
s[ξi,s]
EA
t [ξi,t ]
ph,s −
Ws/Ps
As
29. MODEL Calibration
Financial Shocks
Temporary but persistent increase in the cost of external finance:
ϕt = ¯ϕ × ft , log ft = 0.90 × log ft−1 + ǫf,t , ǫf,t ∼ N(−0.5σ2
f , σ2
f )
Asymmetric shock ⇒ affects the home country only.
Size of the shock: ϕt → 2 ¯ϕ upon impact
30. MODEL Calibration
Calibration Summary
Key Model Parameters Value
Preferences & Technology
strength of deep habits (θ) −0.86
persistence of deep habits (ρ) 0.85
elasticity of substitution b/w and w/i goods (η, ǫ) (2.00,1.50)
fixed operating costs (φ, φ∗) (0.10,0.10)
idiosyncratic volatility (σ) 0.15
Nominal Rigidities
price adjustment costs (γp) 10.0
wage adjustment costs (γw ) 30.0
Financial Frictions
equity dilution costs ( ¯ϕ, ¯ϕ∗), EA
t [ξit ] = 1.16 (0.20,0.02)
31. MODEL SIMULATIONS
Implications of an Asymmetric Financial Shock
Under floating exchange rates (ϕ = 0.20, ϕ∗ = 0.02)
-1.0
-0.5
0.0
0.5
1.0
1.5
pct.
Home
Foreign
(a) Real GDP
0 8 16 24 32
-0.8
-0.4
0.0
0.4
0.8
pps.
(b) Consumption
0 8 16 24 32
-2
-1
0
1
2
pps.
(c) Hours worked
0 8 16 24 32
-1.5
0.0
1.5
3.0
4.5
6.0
7.5
pps.
(d) Interest rate
0 8 16 24 32
-1
0
1
2
3
4
5
pct.
Real
Nominal
(e) Exchange rate
0 8 16 24 32
-0.5
0.0
0.5
1.0
1.5
pps.
(f) Inflation
0 8 16 24 32
-1.6
-0.8
0.0
0.8
1.6
pct.
(g) Exports
0 8 16 24 32
-1.0
-0.5
0.0
0.5
1.0
pct. of GDP
(h) Current account
0 8 16 24 32
NOTE: Exchange rates are expressed as home currency relative to foreign currency.
32. MODEL SIMULATIONS
Implications of an Asymmetric Financial Shock
In a monetary union (ϕ = 0.20, ϕ∗ = 0.02)
-1.0
-0.5
0.0
0.5
1.0
1.5
pct.
Home
Foreign
(a) Real GDP
0 8 16 24 32
-0.8
-0.4
0.0
0.4
0.8
pps.
(b) Consumption
0 8 16 24 32
-2
-1
0
1
2
pps.
(c) Hours worked
0 8 16 24 32
-1.5
0.0
1.5
3.0
4.5
6.0
7.5
pps.
(d) Interest rate
0 8 16 24 32
-1
0
1
2
3
4
5
pct.
Real
Nominal
(e) Exchange rate
0 8 16 24 32
-0.5
0.0
0.5
1.0
1.5
pps.
(f) Inflation
0 8 16 24 32
-1.6
-0.8
0.0
0.8
1.6
pct.
(g) Exports
0 8 16 24 32
-1.0
-0.5
0.0
0.5
1.0
pct. of GDP
(h) Current account
0 8 16 24 32
NOTE: Exchange rates are expressed as home currency relative to foreign currency.
34. MODEL SIMULATIONS
Relative Import Shares
Euro area periphery and core, 2008–2015
0
50
100
150
200
2008 2010 2012 2014
80
90
100
110
120
Index(2008=100) Index(2008=100)
By broad economic categories
Annual
BEC-1 (RHS) BEC-2 (RHS) BEC-3 (LHS)
BEC-4 (RHS) BEC-5 (RHS) BEC-6 (RHS)
BEC-7 (LHS)
2008 2010 2012 2014
85
90
95
100
105
Index(2008=100)
Average
Median
Trade-weighted aggregates
Annual
35. MODEL SIMULATIONS
Financial Heterogeneity and Monetary Union
Alternative calibration: ϕ = ϕ∗ = 0.20
All other parameters are kept at their baseline values.
Financial shocks in both core and periphery.
37. POLICY IMPLICATIONS
Welfare Consequences of a Monetary Union
Heterogeneous financial capacity (ϕ = 0.20, ϕ∗ = 0.02)
Welfare
Monetary Union Flexible FX CE (%)
Home country −259.23 −254.16 2.53
Foreign country −254.05 −254.26 −0.11
Joint −513.28 −508.42 .
40. POLICY IMPLICATIONS
Monetary Union with Complete Risk Sharing
Asymmetric financial shock (ϕ = 0.20, ϕ∗ = 0.02)
-1.0
-0.5
0.0
0.5
1.0
1.5
pct.
Home, baseline
Foreign, baseline
Home, risk sharing
Foreign, risk sharing
(a) Real GDP
0 8 16 24 32
-0.6
-0.3
0.0
0.3
0.6
pct.
(b) Consumption
0 8 16 24 32
-1.0
-0.5
0.0
0.5
pct.
Baseline
Risk sharing
(c) Real exchange rate
0 8 16 24 32
-1.0
-0.5
0.0
0.5
1.0
pct. of GDP
Home
Foreign
(d) Contingent transfer
0 8 16 24 32
NOTE: Exchange rates are expressed as home currency relative to foreign currency.
41. POLICY IMPLICATIONS
Welfare Consequences of a Fiscal Union
Heterogeneous financial capacity (ϕ = 0.20, ϕ∗ = 0.02)
Welfare in a Monetary Union
w/o Risk Sharing w/ Risk Sharing CE (%)
A. Calibration: θ = −0.86, ρ = 0.85, φ∗ = 1.0 × φ
Home country −259.23 −257.61 0.79
Foreign country −254.05 −253.15 0.45
Joint −513.28 −510.76 .
B. Calibration: θ = −0.95, ρ = 0.95, φ∗ = 1.0 × φ
Home country −283.64 −279.86 1.71
Foreign country −278.47 −274.84 1.66
Joint −562.11 −554.80 .
C. Calibration: θ = −0.86, ρ = 0.85, φ∗ = 0.9 × φ
Home country −261.00 −254.69 3.13
Foreign country −248.73 −249.81 −0.56
Joint −509.73 −504.50 .
42. POLICY IMPLICATIONS
Theory of Fiscal Devaluation
Adao, Correia & Teles [2009]; Farhi, Gopinath & Itskhoki [2014]
Some EU countries have considered the idea of swapping VAT and
payroll subsidies:
◮ VAT is a discriminatory tax on imported goods.
◮ For revenue-neutrality, payroll subsidy to domestic firms.
Germany:
◮ Raised VAT (from 16% to 19%) on January 2007
◮ Lowered corporate income tax rate (from 38.7% to 29.8%) on July 2007
(effective January 2008).
43. POLICY IMPLICATIONS
Implementable Plan
We consider a simple VAT-payroll subsidy swap rule
(VAT (τV
t ) + payroll subsidy (ςP
t ))
FD rules that are linear in the resource gap of the home country and
revenue neutral:
τV
t =
∆t
1 + ∆t
∆t = −αFD
× log
yt
¯y
(αFD
> 0)
ςP
t = τV
t × (ph,t ch,t + pf,t cf,t )
◮ Foreign country does not retaliate
◮ Home firms are not subject to the VAT in the foreign country
Is there a region for αFD
that is mutually beneficial to both home and
foreign countries?
44. POLICY IMPLICATIONS
Welfare Implications of Fiscal Devaluations
Monetary union (ϕ = 0.20, ϕ∗ = 0.02)
0
2
4
6
0 10 20 30
Home
Foreign
FD
α
(a) Deep habits:θ = −0.3 and ρ = 0.3
Changeinwelfare
0
2
4
6
0 10 20 30FD
α
(b) Deep habits:θ = −0.86 and ρ = 0.85
Changeinwelfare
0
2
4
6
0 10 20 30FD
α
(c) Deep habits: θ = −0.95 and ρ = 0.95
Changeinwelfare
45. POLICY IMPLICATIONS
Welfare Implications of Fiscal Devaluations
The role of financial frictions
0 10 20 30
0
2
4
6
Change in welfare
( ) FD: The effect of fixed cost
FD
α
0 10 20 30
0
2
4
6
Change in welfare
( ) FD: The effect of issuance cost
FD
α
46. CONCLUSION
Summary
With customer markets, differences in financial capacity across countries
imply a strong amplification mechanism.
Monetary union impedes adjustment of RERs and exacerbates the
downturn in response to an adverse financial shock.
Unilateral fiscal devaluation by periphery may be welfare improving for
both periphery and core.