Using two and a half decades of microdata from the Survey of Construction, we document a robust presale price premium: houses sold before construction commences sell at an average of 2.8% more, with premiums reaching 15% for homes sold five or more months before construction starts. Houses sold post completion of construction also carry a modest 1.4% premium, creating a distinctive U-shaped pricing pattern. To explain this pricing pattern, we develop a search-theoretic model of the housing market in which developers face credit market frictions. We show that these credit frictions give rise to a novel channel that can rationalize the existence of both the presale and post completion premia. A calibration of our economy to the US housing market implies the credit frictions channel can explain about a third of the presale premium.
The corporate bond market provides a vital avenue for firms to cover their borrowing needs. Moreover, the ease with which corporate bonds can be (re)traded in secondary markets affects their liquidity and, effectively, the rate at which corporations can borrow. However, the literature has also pointed out that a well-functioning secondary market can depress money demand and hurt economic activity. We perform a careful quantitative analysis of the channels through which secondary market liquidity affects the real economy in the context of a New Monetarist model. We find that a deterioration in secondary market liquidity has a negative but modest impact on output and unemployment. This small net effect, however, conceals much larger underlying forces that operate in opposite directions and largely offset each other. We also show that the results of our decomposition exercise depend on the inflation rate. Our findings highlight the importance of studying investor portfolios together with asset prices to fully capture the interaction between financial markets and the real economy.
This paper develops a housing search model with endogenous realtor participation and uses it to study the relationship between prices, commission fees, and market liquidity. We show that different price and fee setting mechanisms have first-order implications for prices and liquidity, but not for commission fees. When prices and fees are posted and search is directed, the equilibrium is constrained efficient, whereas under a bargaining regime with random search it is not, even when the Hosios-Mortensen-Pissarides condition holds. A calibrated version of the model shows that commission fees are quantitatively robust to alternative pricing mechanisms, although they are quite sensitive to demand and supply shocks, as well as liquidity shocks. When prices are bargained the equilibrium features 2.5% higher prices, 17% lower sales, and 23% fewer buyers entering the market than the equilibrium under price posting. Our results can thus rationalize why the expected reductions in commission fees and prices did not take place following the recent landmark settlement between the National Association of Realtors and homeowners.
An increasing share of corporate loans, a critical source of firm credit, are sold off of banks' balance sheets and actively traded in a secondary over-the-counter market. We develop a microfounded equilibrium search-theoretic model with labor, credit, and financial markets to study the impact of this secondary loan market on the real economy. Our analysis highlights a policy-relevant trade-off: the market reduces the steady-state level of unemployment by 0.21pp, but it also amplifies unemployment's response to a 1% productivity drop by 0.07pp. Trading delays in the secondary market matter significantly: if trade were instantaneous, steady-state unemployment and its volatility would decline by 1.49pp and by 0.24pp, respectively.
The Diamond-Mortensen-Pissarides model has been the primary workhorse for analyzing the dynamics of unemployment, vacancies, and market tightness over the business cycle. However, it predicts a near-perfect comovement between these variables and labor productivity, whereas the empirical correlation is only mild. We resolve this discrepancy by extending the model to incorporate sunk entry costs and finitely elastic vacancy creation, and by carefully distinguishing between business opportunity destruction and match separation as distinct sources of job loss. These features render vacancies a partially predetermined, positively valued stock variable. If the destruction rate is low, then most vacancies are inherited from the past and reflect historical rather than current productivity, breaking the tight unemployment-productivity link, while preserving strong correlations among labor market variables. We show that, when calibrated to information on job turnover and recall rates, the model reproduces the empirical contemporaneous and dynamic correlations between labor market variables and productivity while preserving the strong correlation between unemployment, vacancies, and the market tightness observed in the data.
This paper studies efficiency in the housing market in the presence of search frictions and endogenous entry of buyers and sellers. These two features are essential to explain the housing market stylized facts and to generate an upward-sloping Beveridge Curve in the housing market. Search frictions and endogenous entry create two externalities in the market. First, there is a congestion externality common to markets with search frictions. Sellers do not internalize the effect of listing a house for sale on other sellers’ probability of finding a buyer. Second, the endogenous entry of buyers leads to a participation externality, as new entrants in the market raise search costs for all buyers. The equilibrium is inefficient even when the Hosios- Mortensen-Pissarides condition holds. Using a calibration to the US housing market, we quantify the size of these externalities and how far the housing market is from the optimal allocation. The optimal vacancy rate and time-to-sell are about half their equilibrium counterparts, whereas the optimal number of buyers and homeowners are above their decentralized equilibrium values. Finally, we investigate how housing market policies restore efficiency in the housing market.
A large literature in macroeconomics concludes that disruptions in financial markets have large negative effects on output and (un)employment. Though diverse, papers in this literature share a common characteristic: they all employ frameworks where money is not explicitly modeled. This paper argues that the omission of money may hinder a model's ability to evaluate the real effects of financial shocks, since it deprives agents of a payment instrument that they could have used to cope with the resulting liquidity disruption. In a carefully calibrated New-Monetarist model with frictional labor, product, and financial markets, we show that the existence of money dampens or even nearly eliminates the real impact of financial shocks, depending on the nature of the shock. We also show that the propagation of financial shocks to the real economy depends on the inflation level: high inflation regimes magnify the real effects of adverse financial shocks.
This paper studies the effects of financial frictions in construction on housing market dynamics. To this end, we build a search-theoretic model of the housing market in which there is endogenous entry of buyers and developers face credit constraints. We capture credit frictions by assuming that developers must search for financing before building a home à la Wasmer and Weil (2004). Our model explores a novel channel that links credit frictions faced by developers to the housing market. We calibrate the model to quantify the size of the credit channel during the 2012–2019 housing market recovery. Through a series of counterfactuals, our model predicts that the credit channel had a large impact on housing liquidity, construction, and the vacancy rate. Furthermore, it accounts for around half of the rise in prices during the 2012-2019 housing market recovery.
The co-movement of buyers and vacancies, i.e. the Beveridge Curve, is a key determinant of the cyclical properties of the housing market. It determines the sign of the correlation between prices and key measures of liquidity such as vacancies (i.e. houses for sale), sales and time-to-sell. As recent work has shown, to account for the core stylized facts of the housing market, search and matching models must be consistent with a positively correlated co-movement of buyers and vacancies—the Beveridge Curve must be upward-sloping. This paper provides empirical evidence that buyers and vacancies are positively correlated along the housing cycle, i.e. that the Beveridge Curve in the housing market is upward sloping. Using data on vacancies and time-to-sell, we construct a series for buyers and estimate the slope of the Beveridge Curve. This approach requires only one minimal structural assumption: the existence of a matching function. The regression results confirm the positive relationship between buyers and vacancies over the business cycle. In addition, we provide an estimate of the elasticity of vacancies with respect to buyers.
In practice, firms face a number of scarce innovation projects. They choose one towards which to direct their effort, but do not coordinate these choices. This gives rise to coordination frictions. This paper develops an expanding-variety endogenous growth model to study the implications of these frictions for growth and welfare. We find that the coordination failure generates a number of foregone innovations and reduces the economy-wide research intensity. Both effects decrease the growth rate. This creates a general equilibrium effect that endogenously amplifies the fraction of wasteful simultaneous innovation. Furthermore, formalizing the coordination frictions uncovers a novel link between the “stepping on toes” and “standing on shoulders” externalities — their magnitudes are endogenously determined through the ratio of firms to innovation projects. We find that the “stepping on toes” externality is larger for all parameter values.
A salient feature of over-the-counter (OTC) markets is intermediation: dealers buy from and sell to customers as well as other dealers. Traditionally, the search-theoretic literature of OTC markets has rationalized this as a consequence of random meetings and ex post bargaining between investors. We show that neither of these are necessary conditions for intermediation. We build a model of a fully decentralized OTC market in which search is directed and sellers post prices ex ante. Intermediation arises naturally as an equilibrium outcome for a broad class of matching functions commonly used in the literature. We further explore, both analytically and numerically, how the extent of intermediation depends on the nature of frictions and model primitives. Our numerical exercises also contrast the model's equilibrium implications to those of a benchmark model with random meetings and ex post bargaining.
Previous research has shown that in the context of a prototypical New Keynesian model, more progressive income taxation may lead to higher volatilities of hours worked and total output in response to a monetary disturbance. We analytically show that this business-cycle destabilization result is overturned within an otherwise identical macroeconomy subject to impulses to the household's utility formulation. Under a continuously or linearly progressive fiscal policy rule with the symmetric-equilibrium tax burden unchanged, an increase in the positive level of tax progressivity will always raise the degree of equilibrium nominal-wage rigidity, and thus serve as an automatic stabilizer that mitigates cyclical fluctuations driven by preference shocks.
This paper develops a model of the housing market with search and credit frictions. The interaction between the two sources of friction gives rise to a novel channel through which the financial sector affects prices and liquidity in the housing market and leads to multiple equilibria. In a numerical exercise, we gauge the relative contribution of credit market shocks to the observed patterns in housing prices, time-to-sell, and mortgage debt-to-price ratio in the U.S. data prior to the 2007 housing market crash. Our results suggest that shocks associated with the credit frictions channel had a relatively larger impact on the observed build-up in mortgage debt and lack of change in time-to-sell than on the increase in prices.
There is ample evidence that R&D investment is mildly pro-cyclical. Whereas the existing literature can explain the positive correlation between investment in R&D and output, the moderate strength of the relationship remains under-explored. This paper develops a stochastic expanding-variety endogenous growth model that accounts for the observed mild pro-cyclicality of R&D. In the model, several firms may simultaneously make the same innovation. Innovations made by many firms simultaneously are of higher quality, on average, and contribute relatively more to the expansion of the knowledge stock in the economy. This delivers an endogenous mechanism that breaks the otherwise perfect correlation between R&D and output. A calibration of our model closely matches the cyclical properties of R&D.
In the context of a prototypical New Keynesian model, this paper examines the theoretical interrelations between two tractable formulations of progressive taxation on labor income versus (i) the equilibrium degree of nominal wage rigidity as well as (ii) the resulting volatilities of hours worked and output in response to a monetary shock. In sharp contrast to the traditional stabilization view, we analytically show that linearly progressive taxation always operates like an automatic destabilizer which leads to higher cyclical fluctuations within the macroeconomy. We also obtain the same business cycle destabilization result under continuously progressive taxation if the initial degree of tax progressivity is sufficiently low.
This paper develops a business cycle model of the housing market with search frictions and entry of both buyers and sellers. The housing market exhibits a well-established cyclical component, which features three stylized facts: prices move in the same direction as sales and the number of houses for sale, but opposite to the time it takes to sell a house. These stylized facts imply that in the data housing vacancies and the number of buyers are positively correlated, i.e. that the Beveridge Curve is upward sloping. A baseline search and matching model of the housing market is unable to match these stylized facts because it inherently generates a downward sloping Beveridge Curve. With free entry of both buyers and sellers, our model reproduces the positive correlation between prices, sales and vacancies, and matches the stylized facts qualitatively and quantitatively.