(5.14)

where Et denotes expectation conditional on information at time t. Comparing equations 5.13 and 5.14 to equations 2.2 and 2.3, it is clear that a monotonic relationship between the marginal utility growth wedge and the tax wedge will hold in this case in expected values.

Thus the complete markets assumption does not affect the general form of our regression based tests.

### 6 Related Literature

Our paper brings together two broad strands of literature in international macroeconomics,
the first pertaining to consumption risk sharing and the second related to taxes in
interna-tional business cycles. The first strand of literature is exemplified by papers such as Backus
et al. (1992, 1994), Backus and Smith (1993), Baxter and Crucini (1995), Stockman and
Tesar (1995), Chari et al. (2002), Kehoe and Perri (2002), and Corsetti et al. (2008), among
many others, that has sought theoretical explanations for the risk-sharing puzzle.^{24} The
main conclusion of this literature is that the consumption correlation anomaly is notoriously
difficult to solve in the absence of enforcement frictions in international financial markets or
strong wealth effects of domestic shocks. Since the framework from which our risk-sharing
tests are derived abstracts from both of these complications, it is not surprising that we
reject the null of perfect risk sharing. Instead our results should be interpreted as evidence
that theoretical models that rely on fluctuations in average tax rates, or fiscal factors in
general, are unlikely to provide a resolution to the consumption risk-sharing puzzle. But,

24Artis and Hoffmann (2008) provide an excellent survey.

accounting for taxes does suggest time series changes in the degree of risk sharing. It follows that accounting for taxes is indeed important for arriving at a correct metric against which the relative success or failure of any one explanation for the risk-sharing puzzle should be compared.

In a separate strand of literature, taxes are considered as a possible reason for which
the marginal product of labor differs from the marginal rate of substitution of consumption
for leisure at any given point in time (for instance, Prescott (2004), Ohanian et al. (2008),
and McDaniel (2011)). Karabarbounis (2014b) uses the same time series on taxes as our
paper to adjust for the level of labor wedges across countries and explores the relevance of
non-separable preferences with home production for international business cycles.^{25}
Karabar-bounis (2014b) notes that time variation in taxes is not relevant for explaining the cyclical
properties of the labor wedge. He shows that, conditional on the noted level adjustment,
when parameters of the home sector are estimated to generate a labor wedge that mimics
its empirical counterpart the standard international business cycle model with complete
as-set markets can match some key stylized facts of the data, including that output is more
correlated than consumption across countries. Our analysis of the role of taxes in
consump-tion risk-sharing, which uses a business cycle accounting approach and regression-based tests
of risk sharing, is complementary to the labor-wedge approach followed by Karabarbounis
(2014b).

Methodologically, we are closest to the large literature that examines empirical measures and tests of risk sharing. Since the seminal work of Cochrane (1991), Mace (1991) and Townsend (1994), a vast literature testing risk sharing at the state and country level has developed, as exemplified by Lewis (1996), Asdrubali et al. (1996), Imbs (2006), Artis and Hoffmann (2008), Flood et al. (2012), among many others. Recent papers in this literature have documented how the degree of risk sharing, as captured by regression-based tests, has evolved over time. The thrust of these papers has been to reconcile the surge in financial globalization in the last two decades with the surprising lack of evidence in favor of improved risk sharing. Explanations have centered around still existent financial frictions and the sta-tistical properties of underlying risks. In contrast, our paper is about a hitherto unexplored source of country specific risk, namely taxes.

### 7 Conclusion

This paper develops an understanding of how, and the extent to which, cross-country dif-ferences and fluctuations in taxes matter for understanding international risk sharing. To the best of our knowledge, this is the first paper in the literature to do so. It well known

25Because these taxes are only available at yearly frequency, he assumes that the same average tax rate holds throughout a year, but his overall analysis is at quarterly frequency.

that, empirically, a lack of international risk sharing is substantially prevalent in the data as measured by a lack of equalization of consumption growth rates across countries. The degree to which such robust international risk sharing fails to manifest itself empirically is puzzling from the point of view of a standard international business cycle model. Indeed, this model predicts that consumption, or its growth rates, should be highly correlated across countries when risk sharing between countries is substantial.

We examine the impact of taxes from two broad vantage points: business cycle ac-counting and regression based tests. Our analysis makes use of panel data on output and consumption. We extend an otherwise standard international business cycle model to ac-count for taxes, making use of cross-ac-country data on average tax rates on consumption and investment expenditures, as well as cross-country data on average taxes on capital and labor income.

Our business cycle accounting perspective allows us to derive the notion of a risk-sharing wedge. This wedge captures the extent to which an international real business cycle model’s risk-sharing condition fails to hold at any point in time, and therefore allows for a dynamic vantage point of risk sharing. The inclusion of taxes in the operationalized model reveals substantial improvements in the degree of international risk sharing over time, especially since the 1980s. We show that this improvement in international risk sharing generally coincides with improvements in financial liberalization. Yet, we also show that this intuitive result is virtually absent when taxes are not incorporated in the analysis. We conclude that accounting for taxes is critical for assessing the correct degree of international risk sharing over time.

Having established the notable implications of taxes for the dynamic behavior of the risk-sharing wedge, we turn to examining the extent to which taxes themselves can explain the lack of risk sharing across countries. We investigate this matter by implementing regression-based tests of international risk sharing. We find that consumption growth differentials are significantly correlated to fluctuations in the level of capital taxes and the growth rate of consumption taxes, as predicted by our theory. However, in spite of this relationship, our analysis leads us to conclude that taxes alone cannot explain the lack of consumption growth-rate equalization across countries since tax growth within and across countries does not display much volatility. Our theory also implies that taxes on labor income and investment expenditure should not have predictive power with respect to consumption growth. However, we find that these two taxes are significantly correlated with consumption growth in the data.

We interpret this finding as evidence that international asset markets are incomplete with respect to the risks related to fluctuations in these two taxes.

It follows that while cross-country differences and fluctuations in taxes are not in them-selves a significant factor limiting risk sharing across countries, accounting for taxes matters for establishing a correct metric for the evolution of risk sharing across time.

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### 8 Appendices

Table 1: Correlation of Per capita Consumption Growth Rates Across Countries

Aus Aut Bel Can Fin Fra Ger Ita Jap Nld Spa Swe Swi UK USA

Aus 1.00

Aut 0.05 1.00 Bel 0.24 0.65 1.00 Can 0.28 0.16 0.26 1.00 Fin 0.28 0.29 0.32 0.34 1.00 Fra 0.23 0.69 0.69 0.26 0.50 1.00 Ger -0.09 0.64 0.58 0.25 0.31 0.71 1.00 Ita 0.19 0.58 0.70 0.14 0.38 0.72 0.56 1.00 Jap 0.04 0.61 0.60 0.08 0.40 0.77 0.63 0.64 1.00 Nld 0.40 0.46 0.54 0.36 0.20 0.57 0.61 0.47 0.34 1.00 Spa 0.32 0.71 0.66 0.41 0.44 0.80 0.59 0.77 0.61 0.57 1.00 Swe 0.34 0.33 0.41 0.46 0.56 0.54 0.39 0.44 0.29 0.35 0.64 1.00 Swi 0.03 0.59 0.61 0.29 0.44 0.72 0.72 0.66 0.61 0.51 0.66 0.36 1.00 UK 0.23 0.15 0.31 0.46 0.40 0.33 0.15 0.26 0.32 0.19 0.39 0.32 0.31 1.00 USA 0.19 0.22 0.22 0.57 0.25 0.37 0.36 0.16 0.30 0.38 0.37 0.28 0.36 0.64 1.00

Notes: Pairwise correlations are calculated for yearly per capita country consumption growth.

Data Source: OECD.

0.8 0.9 1.0 1.1 1.2

1960 1970 1980 1990 2000 2010
**Spain**

1960 1970 1980 1990 2000 2010
**Netherlands**

1960 1970 1980 1990 2000 2010
**Switzerland**

1960 1970 1980 1990 2000 2010
**Sweden**

1960 1970 1980 1990 2000 2010
**UK**

1960 1970 1980 1990 2000 2010
**Australia**

1960 1970 1980 1990 2000 2010
**Belgium**

1960 1970 1980 1990 2000 2010
**Austria**

1960 1970 1980 1990 2000 2010
**Finland**

1960 1970 1980 1990 2000 2010
**Canada**

1960 1970 1980 1990 2000 2010
**Germany**

1960 1970 1980 1990 2000 2010
**France**

1960 1970 1980 1990 2000 2010
**Japan**

1960 1970 1980 1990 2000 2010
**Italy**

Figure 1: Baseline and Consumption Tax Adjusted Wedges. Data sources: OECD and McDaniel (2009).

-1.0 -0.5 0.0 0.5 1.0

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8 Chinn-Ito Index relative to the

United States (right axis) -0.5

0.0 0.5 1.0

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

1960 1970 1980 1990 2000 2010 0.8

Figure 2: Wedge Adjusted for All Taxes and Financial Openness. Data sources: OECD, McDaniel (2009), and Chinn and Ito (2006)

Table 2: Absolute Deviation of Wedges and Bilateral Financial Connectedness

Panel I: Dependent Variable G^{ij}B,t

Variable Name OLS LSDV GMM

G^{ij}B,t−1 0.273*** 0.144*** 0.157***

(0.023) (0.021) (0.024)

Fij,t -0.018 -0.030 -0.046

(0.011) (0.020) (0.045)

R^{2} 0.079 0.171

-No. Obs. 2908 2908 2799

Panel II: Dependent Variable G^{ij}C,t

Variable Name OLS LSDV GMM

G^{ij}C,t−1 0.283*** 0.161*** 0.179***

(0.024) (0.024) (0.026)

Fij,t -0.020* -0.039 -0.040

(0.012) (0.026) (0.049)

R^{2} 0.083 0.179

-No. Obs. 2845 2845 2736

Panel III: Dependent Variable G^{ij}A,t

Variable Name OLS LSDV GMM

G^{ij}A,t−1 0.798*** 0.622*** 0.561***

(0.012) (0.022) (0.026)

Fij,t -0.042** -0.087* -0.339**

(0.0121) (0.047) (0.412)

R^{2} 0.648 0.671

-No. Obs. 2845 2845 2736

Country Fixed Effects No Yes Yes

Year Fixed Effects No Yes Yes

Notes: Coefficient estimates of Regression 4.6 using OLS, LSDV and Arellano-Bond differ-ence GMM. Dependent variables in Panels I, II and III are absolute deviations from unity of the baseline wedge, the consumption tax inclusive wedge, and the all tax inclusive wedge, respectively. Regressors are the lagged dependent variable and a measure of bilateral financial connectedness. See text for details. Robust standard errors, clustered at the country level, in parentheses. Coefficients marked ∗∗∗, ∗∗ and ∗ are significant at 1%, 5% and 10%, respectively.

Data Source: BIS, OECD and McDaniel (2009).

Table 3: The Sensitivity of Domestic Consumption to Domestic Tax Rates: Benchmark

Variable Name No Tax With τ^{c} With τ^{c}, τ^{k} With τ^{c}, τ^{k}, τ^{x}, τ^{h}

X_{it} 0.768*** 0.766*** 0.770*** 0.769***

(0.04) (0.04) (0.04) (0.04)

∆(1 + τ_{it}^{c}) -0.161* -0.160** -0.360***

(0.08) (0.07) (0.09)

ln(1 − τ_{it}^{k}) -0.013 -0.009

(0.01) (0.01)

∆(1 − τ_{it}^{k}) -0.036

(0.02)

∆(1 + τ_{it}^{x}) 0.413***

(0.13)

∆(1 − τ_{it}^{h}) 0.062*

(0.03)

R^{2} 0.7476 0.7503 0.751 0.7541

No. Obs. 745 745 745 745

Country Fixed Effects Yes Yes Yes Yes

Year Fixed Effects Yes Yes Yes Yes

Notes: Coefficient estimates of Regression 5.1. Dependent variable is country consumption
growth between periods t and t − 1. Independent variables are the growth rates of (1) per
capita GDP (X), (2) the gross consumption tax rate (1 + τ^{c}), (3) the investment tax rate (τ^{x}),
and (4) the labor income tax rate (τ^{h}); the natural logarithm of (5) (1 − τ^{k}), where τ^{k} is the
capital income tax rate. Robust standard errors, clustered at the country level, in parentheses.

Coefficients marked ∗ ∗ ∗, ∗∗ and ∗ are significant at 1%, 5% and 10%, respectively. Data Source: OECD and McDaniel (2009).

Table 4: The Sensitivity of International Consumption Differentials to International Tax Rate Differentials: Benchmark

Variable Name No Tax With τ^{c} With τ^{c}, τ^{k} With τ^{c}, τ^{k}, τ^{x}, τ^{h}

Xit− Xjt 0.764*** 0.750*** 0.726*** 0.716***

(0.03) (0.03) (0.02) (0.02)

∆(1 + τ_{it}^{c}) − ∆(1 + τ_{jt}^{c}) -0.248*** -0.255*** -0.517***

(0.06) (0.06) (0.11)

ln(1 − τ_{it}^{k}) − ln(1 − τ_{jt}^{k}) 0.018** 0.022***

(0.01) (0.01)

∆(1 − τ_{it}^{k}) − ∆(1 − τ_{jt}^{k}) -0.063***

(0.01)

∆(1 + τ_{it}^{x}) − ∆(1 + τ_{jt}^{x}) 0.550***

(0.16)

∆(1 − τ_{it}^{h}) − ∆(1 − τ_{jt}^{h}) 0.103**

(0.04)

R^{2} 0.6315 0.6388 0.644 0.6535

No. Obs. 695 695 695 695

Country Fixed Effects Yes Yes Yes Yes

Year Fixed Effects No No No No

Notes: Coefficient estimates of Regression 5.2. Dependent variable is the difference between
country i and j of consumption growth between periods t and t − 1. Country j is always the
United States. Independent variables are the difference between country i and j of the growth
rates of (1) per capita GDP (X), (2) the gross consumption tax rate (1 + τ^{c}), (3) the investment
tax rate (τ^{x}), and (4) the labor income tax rate (τ^{h}); the difference between country i and j of
the natural logarithm of (5) (1 − τ^{k}), where τ^{k} is the capital income tax rate. Robust standard
errors, clustered at the country level, in parentheses. Coefficients marked ∗ ∗ ∗, ∗∗ and ∗ are
significant at 1%, 5% and 10%, respectively. Data Source: OECD and McDaniel (2009).

Table 5: The Sensitivity of Domestic Consumption to Domestic Tax Rates: Non-Additive Labor in Utility Function

Variable Name No Tax With τ^{c} With τ^{c}, τ^{k} With τ^{c}, τ^{k}, τ^{x}, τ^{h}

∆Per capita GDPit 0.758*** 0.756*** 0.761*** 0.760***

(0.04) (0.04) (0.04) (0.04)

∆L_{it} -0.081 -0.081 -0.076 -0.075

(0.14) (0.14) (0.14) (0.14)

∆(1 + τ_{it}^{c}) -0.161** -0.160** -0.361***

(0.07) (0.07) (0.09)

ln(1 − τ_{it}^{k}) -0.012 -0.009

(0.01) (0.01)

∆(1 − τ_{it}^{k}) -0.034

(0.02)

∆(1 + τ_{it}^{x}) 0.417***

(0.13)

∆(1 − τ_{it}^{h}) 0.062*

(0.03)

R^{2} 0.7479 0.7506 0.7512 0.7543

No. Obs. 745 745 745 745

Country Fixed Effects Yes Yes Yes Yes

Year Fixed Effects Yes Yes Yes Yes

Notes: Coefficient estimates of Regression 5.10. Dependent variable is country consumption
growth between periods t and t − 1. Independent variables are the growth rates of (1) per
capita GDP (X), (2) per capita labor hours (L), (3) the gross consumption tax rate (1 + τ^{c}),
(4) the investment tax rate (τ^{x}), and (5) the labor income tax rate (τ^{h}); the natural logarithm
of (6) (1 − τ^{k}), where τ^{k} is the capital income tax rate. Robust standard errors, clustered at
the country level, in parentheses. Coefficients marked ∗ ∗ ∗, ∗∗ and ∗ are significant at 1%, 5%

and 10%, respectively. Data Source: OECD and McDaniel (2009).

Table 6: The Sensitivity of International Consumption Differentials to International Tax Rate Differentials: Non-Additive Labor in Utility Function

Variable Name No Tax With τ^{c} With τ^{c}, τ^{k} With τ^{c}, τ^{k}, τ^{x}, τ^{h}

Xit− Xjt 0.748*** 0.737*** 0.682*** 0.676***

(0.04) (0.04) (0.03 (0.03)

∆L_{it}− ∆L_{jt} -0.139 -0.116 -0.288** -0.272**

(0.12) (0.11) (0.11) (0.10)

∆(1 + τ_{it}^{c}) − ∆(1 + τ_{jt}^{c}) -0.242*** -0.243*** -0.514***

(0.06) (0.05) (0.11)

ln(1 − τ_{it}^{k}) − ln(1 − τ_{jt}^{k}) 0.025*** 0.028***

(0.01) (0.01)

∆(1 − τ_{it}^{k}) − ∆(1 − τ_{jt}^{k}) -0.057***

(0.01)

∆(1 + τ_{it}^{x}) − ∆(1 + τ_{jt}^{x}) 0.563***

(0.17)

∆(1 − τ_{it}^{h}) − ∆(1 − τ_{jt}^{h}) 0.106**

(0.05)

R^{2} 0.6327 0.6396 0.6483 0.6571

No. Obs. 695 695 695 695

Country Fixed Effects Yes Yes Yes Yes

Year Fixed Effects No No No No

Notes: Coefficient estimates of Regression 5.11. Dependent variable is the difference between
country i and j of consumption growth between periods t and t − 1. Country j is always the
United States. Independent variables are the difference between country i and j of the growth
rates of (1) per capita GDP (X), (2) per capita labor hours (L), (3) the gross consumption
tax rate (1 + τ^{c}), (4) the investment tax rate (τ^{x}), and (5) the labor income tax rate (τ^{h}); the
difference between country i and j of the natural logarithm of (6) (1 − τ^{k}), where τ^{k} is the
capital income tax rate. Robust standard errors, clustered at the country level, in parentheses.

Coefficients marked ∗ ∗ ∗, ∗∗ and ∗ are significant at 1%, 5% and 10%, respectively. Data Source: OECD and McDaniel (2009).

Table 7: Summary Statistics of Variables Used in Regressions

Variable Name No. Obs. Mean Std. Dev. Min. Max.

G^{ij}B,t 3465 0.0329935 0.0274149 0.000024 0.1752859

G^{ij}C,t 3399 0.0337833 0.0281799 0.0000031 0.1735971

G^{ij}A,t 3399 0.099514 0.0714455 0.0000633 0.409421

Fij,t 2974 0.0182584 0.0329996 0.000028 0.315706

∆P.C. C_{it} 745 0.0220872 0.0218668 -0.0507903 0.100527

∆P.C. GDPit 745 0.0220793 0.0236309 -0.0923579 0.1008265

∆L_{it} 745 0.0013056 0.0054942 -0.0256427 0.022381

∆(1 + τ_{it}^{c}) 745 0.0008837 0.0074406 -0.0375679 0.0463924
ln(1 − τ_{it}^{k}) 745 -0.2647971 0.0872759 -0.512929 -0.0705729

∆(1 − τ_{it}^{k}) 745 -0.0013337 0.0213322 -0.1206634 0.1118835

∆(1 + τ_{it}^{x}) 745 0.0004252 0.0046853 -0.034612 0.0449434

∆(1 − τ_{it}^{h}) 745 -0.0039873 0.0153218 -0.1184155 0.0876947

∆P.C. Cit− ∆P.C. Cjt 695 0.0017606 0.0232926 -0.0697918 0.0800581

∆P.C. GDP_{it}− ∆P.C. GDP_{jt} 695 0.0040932 0.0242457 -0.0666292 0.1050301

∆L_{it}− ∆L_{jt} 695 0.0014546 0.0063995 -0.0337849 0.0228134

∆(1 + τ_{it}^{c}) − ∆(1 + τ_{jt}^{c}) 695 0.0013748 0.0080512 -0.0360524 0.0479861
ln(1 − τ_{it}^{k}) − ln(1 − τ_{jt}^{k}) 695 0.1325793 0.1157324 -0.1580179 0.4289718

∆(1 − τ_{it}^{k}) − ∆(1 − τ_{jt}^{k}) 695 -0.0052271 0.0305789 -0.1272543 0.1212688

∆(1 + τ_{it}^{x}) − ∆(1 + τ_{jt}^{x}) 695 0.0005836 0.004919 -0.0343993 0.0433238

∆(1 − τ_{it}^{h}) − ∆(1 − τ_{jt}^{h}) 695 -0.0029162 0.0175909 -0.1217293 0.0887701
Notes: ∆ refers to the growth rate of variables, and P.C. to Per Capita variables (for
con-sumption: C, and Gross Domestic Product: GDP). Other variables are: bilateral financial
connectedness (Fij,t) ; absolute deviations from unity of the baseline wedge (G^{ij}B,t), the
con-sumption tax inclusive wedge (G^{ij}C,t), and the all tax inclusive wedge (G^{ij}B,t); consumption tax
rate (τ_{it}^{c}); capital income tax rate (τ_{it}^{k}); investment expenditure tax rate (τ_{it}^{x}); and labor income
tax rate (τ_{it}^{h}). Other details are provided in the text. Data Source: BIS, OECD and McDaniel
(2009).

Figure 3: Scatter Plots of Higher Moments of the Left- and Right-Hand Sides of 2.6.

Notes: The standard deviation, skewness, kurtosis, and autocorrelation of ∆C_{it}− ∆C_{jt}
and [ln(1 − τ_{it}^{k}) − ln(1 − τ_{jt}^{k})] − [∆(1 + τ_{it}^{c}) − ∆(1 + τ_{jt}^{c})] on the vertical and horizontal axes
respectively. Each dot represents a country pair.