Economics

During its history, the ultimate goal of economics has been to develop similar frameworks for modeling economic behavior as invented in physics. This has not been successful, however, and current state of the process is the neoclassical framework that bases on static optimization. By using a static framework, however, we cannot model and forecast the time paths of economic quantities because for a growing firm or a firm going into bankruptcy, a positive profit maximizing flow of production does not exist. Due to these problems, we present a dynamic theory for the production of a profit-seeking firm where the adjustment may be stable or unstable. This is important, currently, because we should be able to forecast the possible future bankruptcies of firms due to the Covid-19 pandemic. By using the model, we can solve the time moment of bankruptcy of a firm as a function of several parameters. The proposed model is mathematically identical with Newtonian model of a particle moving in a resisting medium, and so the model explains the reasons that stop the motion too. The frameworks for modeling dynamic events in physics are thus applicable in economics, and we give reasons why physics is more important for the development of economics than pure mathematics. (JEL D21, O12) Keywords: Limitations of neoclassical framework, Dynamics of production, Economic force, Connections between economics and physics.

We propose a new way to quantify the restrictiveness of an economic model, based on how well the model fits simulated, hypothetical data sets. The data sets are drawn at random from a distribution that satisfies some application-dependent content restrictions (such as that people prefer more money to less). Models that can fit almost all hypothetical data well are not restrictive. To illustrate our approach, we evaluate the restrictiveness of two widely-used behavioral models, Cumulative Prospect Theory and the Poisson Cognitive Hierarchy Model, and explain how restrictiveness reveals new insights about them.

A fundamental result in cake cutting states that for any number of players with arbitrary preferences over a cake, there exists a division of the cake such that every player receives a single contiguous piece and no player is left envious. We generalize this result by showing that it is possible to partition the players into groups of any desired sizes and divide the cake among the groups, so that each group receives a single contiguous piece and no player finds the piece of another group better than that of the player's own group.

The seller of an asset has the option to buy hard information about the value of the asset from an intermediary. The seller can then disclose the acquired information before selling the asset in a competitive market. We study how the intermediary designs and sells hard information to robustly maximize her revenue across all equilibria. Even though the intermediary could use an accurate test that reveals the asset's value, we show that robust revenue maximization leads to a noisy test with a continuum of possible scores that are distributed exponentially. In addition, the intermediary always charges the seller for disclosing the test score to the market, but not necessarily for running the test. This enables the intermediary to robustly appropriate a significant share of the surplus resulting from the asset sale even though the information generated by the test provides no social value.

This paper investigates the reality and accuracy of evolutionary game dynamics theory in human game behavior experiments. In classical game theory, the central concept is Nash equilibrium, which reality and accuracy has been well known since the firstly illustration by the O'Neill game experiment in 1987. In game dynamics theory, the central approach is dynamics equations, however, its reality and accuracy is rare known, especially in high dimensional games. By develop a new approach, namely the eigencycle approach, with the eigenvectors from the game dynamics equations, we discover the fine structure of the cycles in the same experiments. We show that, the eigencycle approach can increase the accuracy by an order of magnitude in the human dynamic hehavior data. As the eigenvector is fundamental in dynamical systems theory which has applications in natural, social, and virtual worlds, the power of the eigencycles is expectedly. Inspired by the high dimensional eigencycles, we suggest that, the mathematical concept, namely 'invariant manifolds', could be a candidate as the central concept for the game dynamics theory, like the fixed point concept for classical game theory.

The random utility model is known to be unidentified. However, there are times when a data set is uniquely rationalizable by the random utility model. We ask the question for which data sets does the random utility model have a unique representation. Our first result characterizes which data sets admit a unique representation. Our second result provides a finite test which determines if a distribution of preferences is observationally equivalent to some other distribution of preferences. We then explore the implications of our results in the context of other random utility models.

Timing decisions are common: when to file your taxes, finish a referee report, or complete a task at work. We ask whether time preferences can be inferred when \textsl{only} task completion is observed. To answer this question, we analyze the following model: each period a decision maker faces the choice whether to complete the task today or to postpone it to later. Cost and benefits of task completion cannot be directly observed by the analyst, but the analyst knows that net benefits are drawn independently between periods from a time-invariant distribution and that the agent has time-separable utility. Furthermore, we suppose the analyst can observe the agent's exact stopping probability. We establish that for any agent with quasi-hyperbolic β,δ -preferences and given level of partial naivete β ^ , the probability of completing the task conditional on not having done it earlier increases towards the deadline. And conversely, for any given preference parameters β,δ and (weakly increasing) profile of task completion probability, there exists a stationary payoff distribution that rationalizes her behavior as long as the agent is either sophisticated or fully naive. An immediate corollary being that, without parametric assumptions, it is impossible to rule out time-consistency even when imposing an a priori assumption on the permissible long-run discount factor. We also provide an exact partial identification result when the analyst can, in addition to the stopping probability, observe the agent's continuation value.

This paper analyzes the role of money in asset markets characterized by search frictions. We develop a dynamic framework that brings together a model for illiquid financial assets `a la Duffie, Garleanu, and Pedersen, and a search-theoretic model of monetary exchange `a la Lagos and Wright. The presence of decentralized financial markets generates an essential role for money, which helps investors re-balance their portfolios. We provide conditions that guarantee the existence of a monetary equilibrium. In this case, asset prices are always above their fundamental value, and this differential represents a liquidity premium. We are able to derive an asset pricing theory that delivers an explicit connection between monetary policy, asset prices, and welfare. We obtain a negative relationship between inflation and equilibrium asset prices. This key result stems from the complementarity between money and assets in our framework.

Data-based decisionmaking must account for the manipulation of data by agents who are aware of how decisions are being made and want to affect their allocations. We study a framework in which, due to such manipulation, data becomes less informative when decisions depend more strongly on data. We formalize why and how a decisionmaker should commit to underutilizing data. Doing so attenuates information loss and thereby improves allocation accuracy.

Always, if the number of states is equal to two; or if the number of receiver actions is equal to two and i. The number of states is three or fewer, or ii. The game is cheap talk, or ii. There are just two available messages for the sender. A counterexample is provided for each failure of these conditions.