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This paper proves the existence of a non‐stationary equilibrium in the canonical search‐and‐matching model with heterogeneous agents. Non‐stationarity entails that the number and characteristics of unmatched agents evolve endogenously over time. An equilibrium exists under minimal regularity conditions and for both paradigms considered in the literature: transferable and nontransferable utility. To address potential discontinuities in match opportunities across types, our analysis introduces a generalized Schauder fixed‐point theorem suitable for models with discontinuous value functions.

PurposeThis paper aims to study the phenomenon known as “house price dispersion”, one of the most important distinctive features of housing markets. House price dispersion refers to the phenomenon of selling two houses with very similar attributes and in near locations at the same time but at very different prices.Design/methodology/approachThis theoretical paper makes use of a search and matching model of the housing market. The search and matching models are the benchmark models of the “matching” markets, such as the labour market and the housing market, where trade is a decentralised, uncoordinated and time-consuming economic activity.FindingsUnlike the previous related literature that attributes to the heterogeneity of buyers and sellers a significant part of the price volatility, in this paper, the house price dispersion depends on the housing tenure status of home-seekers in the house search process. Indeed, in the presence of different housing tenure status of home-seekers, the house search process leads to different types of matching. In turn, this implies different surpluses (the sum of the net gains of the parties involved in the trade), and eventually, different surpluses produce different prices of equilibrium.Research limitations/implicationsAn interesting research agenda for future works would be an extension of the model to study the effect of “online housing search” on the house search and matching process, and thus, on the house price dispersion.Practical implicationsThe main practical implication of this work is that the house price dispersion is an inherent phenomenon in the house search and matching process.Originality/valueNone of the existing and related works of research have considered how to take advantage of the search and matching approach to deal with the phenomenon known as “house price dispersion”, without relying on the ex ante heterogeneity of the parties but looking at the “core” of the house search and matching process.

The paper specifies a simple search and matching model of the labor market and studies how well the model can describe aggregate Croatian labor market dynamics. The model developed is a discrete-time search and matching model with convex vacancy posting costs and two types of shocks: productivity and separation shocks. The model is estimated on unemployment and vacancy data during the period from 2012 to 2020 by using Bayesian methods. The model fits the data well and the estimation shows that productivity shocks are the main driving force of the fluctuations in the labor market, especially for the case of vacancies and output, while the separation shock process accounts for a large percentage of unemployment fluctuations.

In this paper, we re-examine the efficiency of participation with heterogeneous workers in a search-matching model with bargained wages and free entry. Assuming that firms hire their best applicants, we show that participation is always too low. The reason for this is a hold-up phenomenon: to be active, a worker must pay the entire search cost whereas part of the gain from this investment goes to the firm. As a consequence, introducing a (small) minimum wage raises participation, job creation, and employment. Therefore, net aggregate income of the economy is increased.

I discuss the failure of the canonical search and matching model to match the cyclical volatility in the job finding rate. I show that job creation in the model is influenced by wages in new matches. I summarize microeconometric evidence and find that wages in new matches are volatile and consistent with the model's key predictions. Therefore, explanations of the unemployment volatility puzzle have to preserve the cyclical volatility of wages. I discuss a modification of the model, based on fixed matching costs, that can increase cyclical unemployment volatility and is consistent with wage flexibility in new matches.

During the Great Recession, labor markets often exhibit a slow unemployment recovery and persistent outward shifts in the Beveridge curve, which suggests a decline in the efficiency of the job-matching process. While it is often explained by worker search intensity, we argue that the direction of search behavior also matters by proposing a stylized theoretical model based on the Free Energy Principle. Through modeling agents who actively divide their effort between applying for jobs and learning about the market’s new state, our framework shows that agents endogenously shift effort from applications to learning when their uncertainty is high. Building on this micro-foundation, we design a macroeconomic model where matching efficiency is no longer an external parameter but is instead governed by two cognitive factors: the share of unemployed workers with misaligned beliefs and the average learning effort of the informed. Simulation results show that a structural shock will divert effort to learning and depress matching by creating widespread uncertainty, and the subsequent slow recovery is governed by the realignment of collective beliefs. Our work provides a cognitive explanation for this observed persistence of unemployment and the shift of the Beveridge curve.

We develop and estimate a general equilibrium search and matching model that accounts for key business cycle properties of macroeconomic aggregates, including labor market variables. In sharp contrast to leading New Keynesian models, we do not impose wage inertia. Instead we derive wage inertia from our specification of how firms and workers negotiate wages. Our model outperforms a variant of the standard New Keynesian Calvo sticky wage model. According to our estimated model, there is a critical interaction between the degree of price stickiness, monetary policy, and the duration of an increase in unemployment benefits.

By introducing automation development into a labor search model, this paper obtains that the increasing importance of automation in production may be responsible for the reduction in job reallocation along the transitional dynamics path. In the long run, we find automation also increases the total unemployment rate and reduces overall labor force participation. In addition, decreasing any disparity between differently skilled labor is detrimental to job reallocation along the transitional dynamics path, and both the long-run total unemployment rate and overall labor market participation will fall. Nevertheless, appropriate government subsidy policies can improve business dynamics across the labor market.

This paper investigates the impact of an increase in life expectancy on the level and the distribution of income in the presence of skill heterogeneity and automation. It shows analytically that an increase in life expectancy induces the replacement of low-skilled workers by automation capital and high-skilled workers. Moreover, it raises the skill premium and has an ambiguous effect on total income. A simulation exercise, based on US data, shows that an increase in life expectancy raises the level as well as the inequality of income. We consider redistributive policies that can mitigate some of the adverse effects of an increase in life expectancy for low-skilled workers.

We consider statistical inference in games. Each player obtains a small random sample of other players’ actions, uses statistical inference to estimate their actions, and chooses an optimal action based on the estimate. In a sampling equilibrium with statistical inference (SESI), the sample is drawn from the distribution of players’ actions based on this process. We characterize the set of SESIs in large two-action games, and compare their predictions to those of Nash equilibrium, and for different sample sizes and statistical inference procedures. We then study applications to competitive markets, markets with network effects, monopoly pricing, and search and matching markets.