A new principle of international taxation that gives taxing rights on the profits of digital multinational firms (MNEs) has been proposed in Pillar One of the OECD/G20 Base Erosion and Profit Shifting (BEPS) Project. This note delineates this tax principle in a simple model and points out that while the new framework allows taxation of MNEs profits that could not be taxed before, it includes incentives for excessive reductions in the corporate tax rate.
This paper introduces a new approximation scheme for solving high-dimensional semi-linear partial differential equations (PDEs) and backward stochastic differential equa-tions (BSDEs). First, we decompose a target semilinear PDE (BSDE) into two parts,namely dominant linear and small nonlinear PDEs. Then, we apply a Deep BSDEsolver with a new control variate method to solve those PDEs, where approximationsbased on an asymptotic expansion technique are effectively applied to the linear partand also used as control variates for the nonlinear part. Moreover, our theoretical resultindicates that errors of the proposed method become much smaller than those of theoriginal Deep BSDE solver. Finally, we show numerical experiments to demonstrate thevalidity of our method, which is consistent with the theoretical result in this paper.
In this study, we investigate the impact of a transfer program on the earnings of welfare recipients. The case we consider is Public Assistance (PA) in Japan where we can utilize a dataset that contains complete observations of its recipients along with detailed information on their characteristics. Following the literature on the elasticity of taxable income, we also exploit the 2013 reform of the PA system to construct instruments to estimate the earnings responses of PA recipients. With some exceptions, we find small positive price effects and large negative income effects, the latter of which suggests that PA recipients are quite responsive to lump-sum changes in PA benefits. Our study thus highlights the importance of the income effect when we consider earnings responses in the lower tail of income distribution.
In this work, we study an equilibrium-based continuous asset pricing problem which seeks to form a price process endogenously by requiring it to balance the flow of sales-and-purchase orders in the exchange market, where a large number of agents are interacting through the market price. Adopting a mean field game (MFG) approach, we find a special form of forward-backward stochastic differential equations of McKean-Vlasov type with common noise whose solution provides a good approximate of the market price. We show the convergence of the net order flow to zero in the large N-limit and get the order of convergence in N under some conditions. We also extend the model to a setup with multiple populations where the agents within each population share the same cost and coefficient functions but they can be different population by population.
The average labor productivity, ALP, growth rates have declined among developed countries since around 2005. We argue that the declines were caused by the universal technological stagnation, which is reflected in the relative investment price movements. In the last decade, the declines of the relative investment prices have slowed down among developed countries, which was largely driven by equipment prices. We construct a multi-capital growth model and apply a growth accounting decomposition in order to back out the technology of each asset class. Our analysis reveals that the estimated technological stagnation of equipment greatly explains the declines of the ALP growth rate across the developed countries. Technological stagnation is especially severe for the US and explains 77% of the decline of the ALP growth rate after 2005.
We study how government loan programs affect the growth of small businesses by examin-ing a unique policy-based small business lending program in Japan. Combining the loan-level program data with a financial statement database, we find that small business bor-rowers increase employment and asset levels after receiving the loan and that these effectspersist for several years. Differences in debt levels are persistent over time, cash holdings ofloan recipients fall in the long run, and the effects on asset levels are larger in magnitudethan those on employment. In addition, the effects are larger in magnitude for firms iden-tified as financially constrained. These results suggest that the government loan programis successful in relaxing binding financial constraints for small businesses that participatein the program.
The impact of the Industrial Revolution on labor has long attracted the interest of economists as well as economic historians, and recent technological changes and changes in the labor market have newly raised interest in this issue. The accepted view is that technological change in the Industrial Revolution was deskilling and lowered the wage of workers. This paper reexamines this view, by investigating the silk weaving industry in early twentieth-century Japan, which experienced the Industrial Revolution. Power looms, a major technological innovation in the Industrial Revolution, substituted for routine tasks of handloom weavers, and thereby made weavers concentrate on nonroutine tasks, such as stopping looms and supplying warp or weft when it ran out and connecting threads when they broke. Using the model of Autor et al. (2003) and newly constructed plant-level panel data, this paper studies the implications of this change in labor for wages. We find that adoption of power looms was associated with significant increases in the wage of both female and male adult workers, playing a central role in weaving, which suggests the need for revision of the view that technological change in the Industrial Revolution was deskilling.
This paper presents a problem on model uncertainties in stochastic control, in which an agent assumes a best case scenario on one risk and at the same time a worst case scenario on another risk. Particularly, the agent maximizes its view on a Brownian motion, simultaneously minimizing its view on another Brownian motion in choice of a probability measure. This selection method of a probability measure generalizes an approach to model uncertainties in which one considers the worst case scenarios for the views on Brownian motions, such as in the robust control. Specifically, we newly formulate and solve this problem based on a backward stochastic differential equation (BSDE) approach as a sup-inf (resp., inf-sup) optimal control problem on choice of a probability measure with the control domains dependent on stochastic processes. Concretely, we show that under certain conditions, the sup-inf and inf-sup problems are equivalent and these are solved by finding a solution of a BSDE with a stochastic Lipschitz driver. Then, we investigate two cases in which the optimal probability measure is explicitly obtained. The expression of the optimal probability measure includes signs of the diffusion terms of the value process, which are hard to determine in general. In these cases, we show two methods of determining the signs: the first one is by comparison theorems, and the second one is to predetermine the signs a priori and confirm them afterwards by explicitly solving the corresponding equations.
I use new evidence from servant contracts, 1610-1932, to estimate male farm wages and the length of the work year in Japan. I show Japanese laborers were surprisingly poor and could only sustain 2-3 adults relative to 7 adults for the English. Japanese wages were the lowest among pre-industrial societies and this was driven by Malthusian population pressures. I also estimate the work year and find peasants worked 325 days a year by 1700, predating the industrious revolution in Europe. The findings imply Japan had a distinct labor-intensive path to industrialization, utilizing cheap labor over a long work year.
This study investigates the peer effects of a speed competition on educational outcomes in self-learning at the right level program for primary school students in Bangladesh. Specifically, we examine the peer effects of speed of problem-solving (time) on math scores (score) using students’ daily progress record over eight months. The unique setting of the program allows to address the identification challenges such as the direction of causality and the reflection problem. The results show a significant peer effect of classmates’ speed on improving one’s own time. Furthermore, we find that the faster the classmates of similar abilities, the higher one’s own math scores. This suggests that the speed competition among students with similar abilities leads to improving their learning quality without negatively affecting others. These findings will contribute to shaping an effective learning environment by incorporating positive peer pressure on learning quality.
We examine bond auctions in the Philippines by using bid data from around 500 Treasury auctions. The Philippines features a strategic auctioneer who uses both discriminatory and uniform-price auctions, and actively manages supply. Here, discriminatory auctions generate lower borrowing costs, but at the expense of con- centrating awards among fewer bidders. We observe that the decision to restrict supply is driven by cost and strength of demand. Bidders adjust for winner's curse by submitting bids with higher yield spreads in response to higher volatility and more competitors. Though bidder heterogeneity exists, average auction profits do not significantly differ across bidder types.
We explore the theoretical properties of public good provision under the complementarity between safety and private/public good consumption. The presence of the mobile worker generates fiscal externality, making the equilibrium ineffcient. The direction of ineffciency is determined by three factors: the characteristics of the utility function, the difference in income between the immobile and mobile workers, and the immobile worker's marginal utility of hosting another mobile worker. We show that the complementarity between safety and private good consumption plays a crucial role in determining the impacts of the third factor whereas the complementarity between safety and public good does not.
We present a model of the music industry including artists, consumers and platforms. Artists are heterogeneous in their degree of ex-ante popularity and each one has two sources of income: songs and concerts. However, only for the unknown artists there is a link between the number of songs sold (diffusion) and the revenue from concerts. Copies of the songs of the artists are hosted in platforms. The for-profit platform chooses a positive price to sell high-quality copies, whereas the open platform offers low-quality copies for free. We compare the equilibrium outcomes and welfare with copyright and with piracy. We find that the unknown artists prefer piracy more often than the famous artists, that the price charged by the for-profit platform does not necessarily decrease with piracy, and that piracy may damage the social welfare when the vertical differentiation is large enough.
In the stochastic volatility models for multivariate daily stock returns, it has been found that the estimates of parameters become unstable as the dimension of returns increases. To solve this problem, we focus on the factor structure of multiple returns and consider two additional sources of information: first, the stock index associated with the market factor and, second, the realized covariance matrix calculated from high-frequency data. The proposed dynamic factor model with the leverage effect and realized measures is applied to 10 top stocks composing the exchange traded fund linked with the investment return of the S & P 500 index and the model is shown to have a stable advantage in portfolio performance.
This paper explores the implications of technological change on the wages and skills of workers in early twentieth-century Japan. The Japanese economy experienced essential elements of the industrial revolution, such as the adoption of the factory system and mechanization, in this period. Exploiting detailed plant-level data on the silk weaving industry, we compare wage and composition of workers between powered plants and non-powered plants. We found that (a) the wage, (b) the relative wage of male adult workers to female adult workers, and (c) the ratio of male workers, were all higher at powered plants than non-powered plants. (a) reflects the higher marginal productivity of labour, while (b) and (c) reflect the emergence of a new type of skilled worker, i.e. mechanics.
This paper empirically investigates how competition affects physicians' opportunistic behavior in the context of the utilization of MRI scanners. We examine micro-panel data on Japanese hospitals, where we observe how physicians change their usage of MRI scanners in response to MRI adoption by nearby hospitals. We identify competition-driven physician-induced demand: Hospitals lose patients because of MRI adoption by nearby hospitals, and, to compensate for this loss, physicians perform more MRI scans per patient. Although competition may benefit consumers through better access to MRI scanners, it also causes additional physician-induced demand.
An efficient simulation-based methodology is proposed for the rolling window esti- mation of state space models. Using the framework of the conditional sequential Monte Carlo update in the particle Markov chain Monte Carlo estimation, weighted particles are updated to learn and forget the information of new and old observations by the forward and backward block sampling with the particle simulation smoother. These particles are also propagated by the MCMC update step. Theoretical justifications are provided for the proposed estimation methodology. The computational performance is evaluated in illustrative examples, showing that the posterior distributions of model parameters and marginal likelihoods are estimated with accuracy. Finally, as a special case, our proposed method can be used as a new sequential MCMC based on Particle Gibbs, which is the promising alternative to SMC2 based on Particle MH.
This study indicates that the improper uses of a public blockchain disable real-world governance in organizations and marketplaces. By using any basic application of smart contracts, such as escrow transactions, along with a revelation mechanism outside the blockchain, individuals can execute illegal cartel acts in a self-enforcing and non-judicial manner. Cartel members can then implement collective deviations without help from trusted intermediaries or any requirements on reputation or word-of-honor. We show that a first price auction is vulnerable to cartel threats even if the seller can hide bidders' prices because bidders take a countermeasure to hidden prices by using blockchain.
Centralized matching mechanisms and decentralized markets have been widely studied to allocate indivisible objects. However, they have been analyzed separately. The present paper proposes a new framework, by explicitly formulating a two-stage model where objects are allocated through a matching mechanism in the first stage and traded in the second stage market. In addition, one divisible good called money may or may not be available in the market. Every player demands at most one unit of object besides money. The players may face different priorities at each object type in the first stage. Each object type has a limited amount of capacity, called quota. Each player has a quasi-linear utility function. The present analysis sets forth the equivalence conditions under which stability and efficiency are attained in equilibrium.
