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Exploiting the exogenous and regional nature of the Great East Japan Earthquake of 2011, this paper provides a quantification of the role of input-output linkages as a mechanism for the propagation and amplification of shocks. We document that the disruption caused by the disaster propagated upstream and downstream supply chains, affecting the direct and indirect suppliers and customers of disaster-stricken firms. Using a general equilibrium model of production networks, we then obtain an estimate for the overall macroeconomic impact of the disaster by taking these propagation effects into account. We find that the earthquake and its aftermaths resulted in a 0:47 percentage point decline in Japan���s real GDP growth in the year following the disaster., European Research Council under the grant ���Production Networks in Macroeconomics���(#RG72699) and the Senior Keynes Fellowship, University of Cambridge

Using a dataset that recorded a large number of investment transactions in China from 1991 to 2018, we examine the statistical properties of the Chinese venture capital (VC) syndication network. Our main findings are as follows. First, the number of investment transactions sharply increased after 2014. Second, more than half of the VC firms are located in Beijing, Shanghai, and Shenzhen. Third, the degree distribution becomes roughly straight on a log–log plot. Fourth, the hypothesis that the degree distribution follows a power-law distribution is not rejected for 2015 and 2016. Fifth, better connected VC firms increase their connectivity faster, which suggests the existence of preferential attachment.

Nirei and Scheinkman (2021) proposed an equilibrium model of price adjustments with menu-costs with a finite number of firms and derived a “reproduction number” for repricing and a limit functional form for the distribution of the number of simultaneously price-adjusting firms. We show that the distribution of price-changes in data from the Billion Prices Project is well fitted by this functional form and exhibits a reproduction number that is close to unity, indicating that complementarity in price-changes plays a major role in repricings.

This study provides an explanation for the emergence of power laws in asset trading volume and returns. We consider a two‐state model with binary actions, where traders infer other traders' private signals regarding the value of an asset from their actions and adjust their own behavior accordingly. We prove that this leads to power laws for equilibrium volume and returns whenever the number of traders is large and the signals for asset value are sufficiently noisy. We also provide numerical results showing that the model reproduces observed distributions of daily stock volume and returns.

In this Supplementary Appendix, we extend the baseline model of "Repricing Avalanches" to the case where productivity is not constant. Even though some portions are straightforward extension of the baseline model, we allow for some overlap with the main text for the sake of a self-contained exposition of the extended model.

We construct a tractable neoclassical growth model that generates Pareto's law of income distribution and Zipf's law of the firm size distribution from idiosyncratic, firm-level productivity shocks. Executives and entrepreneurs invest in risk-free assets, as well as their own firms' risky stocks, through which their wealth and income depend on firm-level shocks. By using the model, we evaluate how changes in tax rates can account for the evolution of top incomes in the United States. The model matches the decline in the Pareto exponent of the income distribution and the trend of the top 1 percent income share in recent decades. (JEL D31, H24, L11)

We construct a neoclassical growth model with heterogeneous households that accounts for the Pareto distributions of income and wealth in the upper tail. In an otherwise standard Bewley model, we feature households' business productivity risks and borrowing constraints, which we find generate the Pareto distributions. Households with low productivity rely on wages and returns from safe assets, while high productivity households choose not to diversify their business risks. The model can quantitatively account for the observed income distribution in the U.S. under reasonable calibrations. Furthermore, we conduct several comparative statics to examine how changes in parameters affect the Pareto distributions. In particular, we find that the change in the top tax rates in the 1980s potentially accounts for much of the observed increase in top income dispersion in the last decades. Our analytical result provides a coherent interpretation for the numerical comparative statics.

This paper argues that interactions of firms account for a sizable part of fluctuations in aggregate investments without exogenous aggregate shocks. We first establish empirically that the fraction of firms that engage in a lumpy investment follows a non-normal, two-sided exponential distribution across region-year with a panel data set of Italian firms. We then present a simple sectoral model that generates the two-sided exponential distribution that arises from the complementarity of the firms’ lumpy investments within a region. Calibrated by the firm-level estimate of complementarity, the model is capable of generating the two-sided exponential fluctuations observed at the aggregate level.

We present a state-dependent pricing model that generates inflation fluctuations from idiosyncratic shocks to the cost of price changes of individual firms. A firm's nominal price increase, lowers other firms' relative prices, thereby inducing further nominal price increases. This snow-ball effect of repricing causes fluctuations to the aggregate price level without exogenous aggregate shocks. The fluctuations caused by this mechanism are more volatile when the density of firms at the repricing threshold is high, and the density at the threshold is high when the trend inflation level is high. Thus, the model implies that higher trend inflation produces larger volatility of short-term inflation rates. Analytical and numerical analyses show that the model can account for the positive relationship between inflation level and volatility that has been observed empirically.

This study demonstrates that the interactions of firm-level indivisible investments give rise to aggregate fluctuations without aggregate exogenous shocks. When investments are indivisible, aggregate capital is determined by the number of firms that invest. I develop a method to derive the closed-form distribution of the number of investing firms when each firm’s initial capital level varies stochastically. This method shows that idiosyncratic shocks may lead to nonvanishing aggregate fluctuations when the number of firms tends to infinity. I incorporate this mechanism in a dynamic general equilibrium model with indivisible investment and predetermined goods prices. The model features no aggregate exogenous shocks, and the fluctuation is driven by idiosyncratic productivity shocks. Numerical simulations show that the model generates aggregate fluctuations comparable to the business cycles in magnitude and correlation structure under standard

In science, research teams are increasing in size, which suggests that science is becoming more organisational. This paper aims to empirically investigate the effects of the division of labour in management and science on serendipity, which has been considered one of the great factors in science. Specifically, in examining the survey of scientists conducted in Japan and the U.S., this paper treats the following questions: Does pursuing serendipity really bring about better scientific outcomes? How does the division of labour in science influence serendipity and publication productivity? The empirical results suggest that serendipity actually brings about better research quality on average. It also finds that if the managerial role is played by a leading scientist in the team, this is positively associated with the quality of the paper through allowing researchers to pursue serendipitous findings. In contrast, if the managerial role and leading research role are played by different members, this has a positive association with the number of papers published, as the project size becomes larger. These results indicate there is a trade-off between serendipity and publication productivity in science via who plays the leading role in research and management.

Loan syndication increases bank interconnectedness through co-lending relationships. We study the financial stability implications of such dependency on syndicate partners in the presence of shocks to banks' capital. Model simulations in a network setting show that such shocks can produce rare events in this market when banks have shared loan exposures while also relying on a common risk management tool such as value-at-risk (VaR). This is because a withdrawal of a bank from a syndicate can cause ripple effects through the market, as the loan arranger scrambles to commit more of its own funds by also pulling back from other syndicates or has to dissolve the syndicate it had arranged. However, simulations also show that the core-periphery structure observed in the empirical network may reduce the probability of such contagion. In addition, simulations with tighter VaR constraints show banks taking on less risk ex-ante.

We introduce a stochastic model for order book dynamics in online product markets, where product prices basically follow a random walk, but sometimes exhibit a sharp decline like cascade. In this model, each e-retailer stochastically places a limit sell order, stochastically reviews its quote price, and revise the quote price if necessary. On the other hand, customers stochastically pick a particular e-retailer and purchase its product. We conduct a numerical simulation to show that the model succesfully reproduces some important facts regarding price dynamics in online product markets, including a Hurst exponent around 0.5, non-autocorrelation of price fluctuations, non-trivial complex correlation of the sign of price changes, and the fat tails of price change distributions.

Tails in the distribution of JPY/USD exchange rate returns are well approximated by an exponentially dampened power-law. Distribution parameter estimates indicate that yen appreciation jumps belong to a Levy process with unbounded variation, suggesting that same mechanism may be responsible for fluctuations in normal times as well as rare crashes. In contrast, yen depreciation jumps have a well defined second moment suggesting a Gaussian regime. In addition, extreme episodes of yen appreciation are larger and more persistent than episodes of yen depreciation. The asymmetry is magnified and power-law tails are more elongated during times of higher interest rate differential between U.S. and Japan and higher level of VIX indicating that carry trade may be the driver. We propose a model of strategic carry trader behavior that in equilibrium generates exponentially dampened power-law distribution of jumps in foreign exchange along with “up by the stairs down by the elevator” dynamics arising from the assymetries between negative and positive jumps.

We investigate retailers’ price setting behavior using a unique dataset containing by-the-second records of prices offered by closely competing retailers on a major Japanese price comparison website. First, we find that, when the average price of a product across retailers falls rapidly, the frequency of price adjustments increases, and the size of price adjustments becomes larger. Second, we find positive autocorrelation in the frequency of price adjustments, implying that there tends to be clustering where price adjustments occur in succession. In contrast, there is no such autocorrelation in the size of price adjustments. These two findings indicate that the behavior of competing retailers is characterized by state-dependent pricing rather than time-dependent pricing.

This paper explains the fat-tail distribution of asset transaction volumes and prices by a model of rational herd behavior of traders. Each trader decides whether to buy an asset by observing private information and other traders’ actions. A trader’s buying action reveals his positive private information and affects the other traders’ beliefs in favor of buying, leading to strategic complementarity. A power-law distribution emerges for the number of buying actions in a static Nash equilibrium. This model provides an economic reason as to why the stock market has to exhibit a criticality in the connectivity of the traders’ actions.

Exploiting the exogenous and regional nature of the Great East Japan Earthquake of 2011, this paper provides a systematic quantification of the role of input-output linkages as a mechanism for the propagation and amplification of shocks. We document that the disruption caused by the earthquake and its aftermaths propagated upstream and downstream supply chains, affecting the direct and indirect suppliers and customers of disaster-stricken firms. We then use our empirical findings to obtain an estimate for the overall macroeconomic impact of the shock by taking these propagation effects into account. We find that the propagation of the shock over input-output linkages can account for a 1.2 percentage point decline in Japan’s gross output in the year following the earthquake. We interpret these findings in the context of a general equilibrium model that takes the firm-to-firm linkages into account explicitly.

The definitive version is available at onlinelibrary.wiley.com, This paper analyzes empirical income distributions and proposes a simple stochastic model to explain the stationary distribution and deviations from it. Using the individual tax returns data in the U.S. and Japan for 40 years, we rst summarize the shape of income distribution by an exponential decay up to about the 90th percentile and a power decay for the top 1 percent. We then propose a minimal stochastic process of labor and asset income to reproduce the empirical characteristics. In particular, the Pareto exponent is derived analytically and matched with empirical statistics.

This paper quantifies the effects of precautionary savings. It demonstrates that Zeldes' estimate (1989) of excess consumption growth for low asset holders is consistent with a dynamic general equilibrium model with uninsurable endowment shocks when borrowing is constrained at three months' worth of average wage income. I propose a Monte Carlo simulation of the stationary equilibrium as a method of indirectly testing the hypotheses of a no-borrowing specification and a natural debt limit specification. At the estimated borrowing constraint, an increase in endowment shocks within the range of empirical findings can cause a 1.6% increase in the savings rate and a 6.9% increase in capital. (Copyright: Elsevier)

We construct a tractable neoclassical growth model that generates Pareto's law of income distribution and Zipf's law of the firm size distribution from idiosyncratic, firm-level productivity shocks. Executives and entrepreneurs invest in risk-free assets as well as their own firms' risky stocks, through which their wealth and income depend on firm-level shocks. By using the model, we evaluate how changes in tax rates can account for the evolution of top incomes in the U.S. The model matches the decline in the Pareto exponent of the income distribution and the trend of the top 1% income share in recent decades.

This study examines the response of aggregate consumption to active labor market policies that reduce unemployment. We develop a dynamic general equilibrium model with heterogeneous agents and uninsurable unemployment as well as policy regime shocks to quantify the consumption effects of policy. By implementing numerical experiments using the model, we demonstrate a positive effect on aggregate consumption even when the policy serves as a pure transfer from the employed to the unemployed. The positive effect on consumption results from the reduced precautionary savings of the households who indirectly benefit from the policy by a decreased unemployment hazard in future.

Using a simultaneous-move herding model of rational traders who infer other traders' private information on the value of an asset by observing their aggre- gate actions, this study seeks to explain the emergence of fat-tailed distributions of transaction volumes and asset returns in financial markets. Without mak- ing any parametric assumptions on private information, we analytically show that traders' aggregate actions follow a power law distribution. We also provide simulation results to show that our model successfully reproduces the empirical distributions of asset returns. We argue that our model is similar to Keynes's beauty contest in the sense that traders, who are assumed to be homogeneous, have an incentive to mimic the average trader, leading to a situation similar to the indeterminacy of equilibrium. In this situation, a trader's buying action causes a stochastic chain-reaction, resulting in power laws for financial fluctuations.

This paper presents a tractable dynamic general equilibrium model of income and firm-size distributions. The size and value of firms result from idiosyncratic, firm-level productivity shocks. CEOs can invest in their own firms’ risky stocks or in risk-free assets, implying that the CEO’s asset and income also depend on firm-level productivity shocks. We analytically show that this model generates the Pareto distribution of top income earners and Zipf’s law of firms in the steady state. Using the model, we evaluate how changes in tax rates can account for the recent evolution of top incomes in the U.S. The model matches the decline in the Pareto exponent of income distribution and the trend of the top 1% income share in the U.S. in recent decades. In the model, the lower marginal income tax for CEOs strengthens their incentive to increase the share of their firms’ risky stocks in their own asset portfolios. This leads to both higher dispersion and concentration of income in the top income group.

This paper proposes a new model of self-organized criticality in order to explain large fluctuations of aggregate production in an (S,s) economy. It is shown that the inventory distribution in an (S,s) economy always converges to a unique steady state, and that aggregate production exhibits a peculiar instability at the steady state: the propagation effect of a demand shock on aggregate production follows a power law. The model differs from previous models of self-organized criticality in that it incorporates a global interaction in the network. The global interaction is interpreted as a representation of market transactions with which economists are familiar. The other novelty of the paper is that an intrinsic instability of (S,s) economies is found. Many small non-linearities in the (S,s) economy may not be cancelled out in aggregation. Instead, they play a key role in organizing the fluctuations of aggregate production.

Individual threshold behaviors generate large endogenous fluctuations in a globally interactive network. In a version of NK models, the bonds are allowed to be allocated randomly across nodes in each period. It is shown that the aggregate output asymptotically follows a branching process with martingale property on a unique globally stable state.

A new model of self-organized criticality is defined by incorporating a random network model in order to explain endogenous complex fluctuations of economic aggregates. The model can feature many globally interactive systems such as economies or societies.

This paper quantifies the spillover effect of local exogenous shocks, such as earthquakes, to other firms through supply chain networks. Combining micro data on a large-scale inter-firm transaction network and geographic information on firm location, we examine the firm level impact of supply chain disruptions occurring in the aftermath of the Great East Japan Earthquake in 2011. When we focus on exiting firms in affected areas as the originating firms of spillovers, we find that sales growth of linked firms outside the area exhibits negative and significant effects for both upstream and downstream firms. Furthermore, the significantly negative effects on downstream firms are shown not only for directly linked firms but also indirectly connected firms with degrees of separation 2, 3, 4, and 5.

This study seeks to explain the emergence of fat-tailed distributions of trading volumes and asset returns in financial markets. We use a rational expectations form of the herding model. In the model, traders infer other traders' private signals regarding the value of an asset by observing their aggregate buying actions. The rational expectations equilibrium outcome entails an upward sloping demand curve. This is because the information contained in others' signals is more encouraging than is reflected in the incremental price. That is, there are strategic complementarities in informed traders' buying actions. In this environment, we show that equilibrium trading volumes and asset returns follow fat-tailed distributions without making any parametric assumptions on private signals. Specifically, we demonstrate that the trading volume follows a power-law distribution when the number of traders is large and the signal is noisy. Furthermore, we provide simulation results to show that our model successfully reproduces the observed distributions of daily stock returns.

We capture key features of the syndicated loan market in a micro-founded model, which allows a bottom-up analysis of equilibrium adjustments to shocks. Model simulations, calibrated to empirical data, indicate that common equity shock is the most evident driver of the rare events in the market. The resulting emergence of long tail in the aggregate distribution of withdrawals and dissolved loans is robust to alternative shock distributions and network topologies. Yet, the empirical network degree distribution points at the core-periphery structure, which is more localized than the random network, so might subdue systemic events. Furthermore, an experiment of a targeted shock within the empirical network suggests that the failure of a highly interconnected bank may not necessarily generate a large systemic event in this market.

We estimate a structural model of herding behavior in which feedback arises due to mutual concerns of traders over the unobservable "true" level of market liquidity. In a herding regime, random shocks are exacerbated by endogenous feedback, producing a dampened power-law in the fluctuation of largest sales. The key to the fluctuation is that each trader responds not only to private information, but also to the aggregate behavior of others. Applying the model to the data on portfolios of institutional investors (fund managers), we find that the empirical distribution is consistent with model predictions. A stock's realized illiquidity propagates herding and maps onto the dampening parameter of the probability distribution of the number of fund managers choosing to drop the stock from their portfolio each quarter. The distribution function itself has desirable properties for evaluating "tail risk."

This paper demonstrates that a generic herd behavior model generates a fat-tailed distribution of traders' aggregate actions. We consider a simultaneous-move game of traders who infer other traders' private information on the value of assets by observing their actions and decide whether to buy the asset or not. The number of buying actions in a Bayesian Nash equilibrium is characterized by a sum of a binomial process by introducing a fictitious tatonnement. Under a broad class of distributions for the private information, we show that the aggregate actions follow a power-law distribution with an exponential truncation. The empirical distribution of the daily returns of S&P 500 stocks is fitted by the model prediction, when the aggregate actions are translated into price movements either by an empirical volume-price impact function or by a market-maker who sets the price by incorporating the available information. This model nests the benchmark herd behavior model and the recent models of critical phenomena in the network of traders. The latter showed that the aggregate actions follow a power-law tailed distribution when the connectivity of networked traders is set at a critical level. In this context, we provide an economic reason why at all the rational herding behavior exhibits criticality in a general setting. Suppose that a good private information leads a trader to buy, whereas the other traders do not buy despite their observation of the action. Then their inactions reveal their private information partially. The total impact of the action on the revealed information is thus of order 1/N, where N is the total number of traders, if the private information is equally informative across the traders. When this is the case, the mean impact of the initial action on the other actions is roughly equal to one. The tatonnement triggered by the initial action becomes a martingale, in which the distribution of the total number of buying actions during the tatonnement exhibits a power-law tail. We further show that, when the static game is repeated over time, the triggering action almost surely occurs and the mean impact of the action in the chain reaction evolves toward the critical level. This implies that the rational learning of traders self-organizes their beliefs to the critical state at which a power-law clustering of actions emerges.

This paper proposes a model of endogenous fluctuations in investment. A monopolistic producer has an incentive to invest when the aggregate demand is high. The investment at the firm level is also known to exhibit a threshold behavior called an (S,s) policy. These two facts lead us to consider that the fluctuation in aggregate investment is generated by the global coupling of the non-linear oscillators. From this perspective, we characterize the probability distribution of the investment clustering in a partial equilibrium of product markets, and show that its variance can be large enough to match the observed investment fluctuations. We then implement this mechanism in a dynamic general equilibrium model to explore an investment-driven business cycle. By calibrating the model with the SIC 4-digit level industry data, we numerically show that the model replicates the basic structure of the business cycles.

Personal income distributions in Japan are analyzed empirically and a simple stochastic model of the income process is proposed. Based on empirical facts, we propose a minimal two-factor model. Our model of personal income consists of an asset accumulation process and a wage process. We show that these simple processes can successfully reproduce the empirical distribution of income. In particular, the model can reproduce the particular transition of the distribution shape from the middle part to the tail part. This model also allows us to derive the tail exponent of the distribution analytically.

This paper examines a stochastic multiplicative process with reset event to explain the power law in the tail of personal income distribution. The tail part of the income distributions in post-war Japan persistently exhibits a power-law distribution with an exponent around 2. We find that a multiplicative process with reset events can explain this pattern. By using a default rate of corporate fundings as a hazard rate of the reset event, we obtain the correct exponent for the power-law in Japanese income.

This paper proposes a model of endogenous fluctuations in investment. A monopolistic producer has an incentive to invest when the aggregate demand is high. This causes a propagation of investment across sectors. When the investment follows an (S,s) policy, the propagation size can exhibit a significant fluctuation. We derive the probability distribution of the propagation size, and show that its variance can be large enough to match the observed investment fluctuations. We then implement this mechanism in a dynamic general equilibrium model to explore an investment-driven business cycle. By calibrating the model with the SIC 4-digit level industry data, we numerically show that the model replicates the basic structure of the business cycles. Recent empirical studies discover that the establishment level investment exhibits a lumpy behavior (cf. Doms and Dunne (RED 1998) and Cooper, Haltiwanger, and Power (AER 1999)). This behavior suggests that a firm follows an (S,s) policy due to a fixed cost of investments. This empirical finding has stimulated the macroeconomic investigation whether such an (S,s) investment at the firm level causes the aggregate fluctuations (cf. Caballero and Engel (Econometrica 1999) and Thomas (JPE 2002)). We consider the case when the investments of industries are strategically complement each other. Each good is produced by a monopolist, and all the goods are used as inputs to produce each good. If the strategic complementarity is too small, then the aggregate follows the law of large numbers even though the individual behavior is non-linear. If the strategic complementarity is too large, then the multiple equilibria emerge (cf. Shleifer (JPE 1986)). We show that the aggregate exhibits a modest fluctuation such as seen in the business cycles when the strategic complementarity is about the same magnitude of the micro-level fluctuations. The aggregate fluctuation is driven by the stochastic size of investment propagation across industries. Suppose that there are N industries. We obtain two analytical results. First, when the strategic complementarity is of order 1/N, we obtain the distribution function of the investment propagation size. The distribution follows a power-law distribution exponentially truncated in the tail. The variance of the aggregate fluctuation is much larger than its smoothly-adjusting counterpart. This contrasts with the "neutrality" theorem by Caplin and Spulber (QJE 1987) and Caballero and Engel (Econometrica 1991) which shows that the individual (S,s) behavior does not add up to the aggregate fluctuations due to the law of large numbers. Secondly, the aggregate variance does not depend on N when the strategic complementarity is exactly 1/N. This case corresponds to the constant returns to scale technology and the rigid wage and interest in the N-sector production model. This result shows the possibility of an endogeneous fluctuation of the aggregate production driven by the propagation of sectoral investments. Our scale-free aggregate fluctuation is caused by the feedback effect among individual non-linear behaviors. This mechanism can be seen as a generalization of the self-organized criticality proposed by Bak, Chen, Scheinkman, and Woodford (Ricerche Economiche 1993). The propagation process is dampened by the general equilibrium effect of flexible wage and interest or the decreasing returns to scale. We obtain the power-law distribution only when these dampening forces are nullified. The robustness of our fluctuation result in a general equilibrium setup has to be investigated by numerical simulations. We simulate a dynamic general equilibrium model which incorporates the investment propagation mechanism above. The magnitude and periodicity of the sectoral (S,s) behavior is calibrated by data on the SIC 4-digit U.S. manufacturing sectors. When the representative household's preference on consumption and leisure is sufficiently close to linear, we obtain the second moment properties of aggregate production, consumption, and investment that mimic those of the U.S. business cycles

This paper presents a tractable dynamic general equilibrium model of income and firm-size distributions. The size and value of firms result from idiosyncratic, firm-level productivity shocks. CEOs can invest in their own firms¡¯ risky stocks or in risk-free assets, implying that the CEO's asset and income also depend on firm-level productivity shocks. We analytically show that this model generates the Pareto distribution of top income earners and Zipf¡¯s law of firms in the steady state. Using the model, we evaluate how changes in tax rates can account for the recent evolution of top incomes in the U.S. The model matches the decline in the Pareto exponent of income distribution and the trend of the top 1% income share in the U.S. in recent decades. In the model, the lower marginal income tax for CEOs strengthens their incentive to increase the share of their firms¡¯ risky stocks in their own asset portfolios. This leads to both higher dispersion and concentration of income in the top income group. Length: 54 pages