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In this paper, a previously proposed method for story stiffness estimation of steel residential house is extended to estimate story stiffness of wooden residential houses considering non‐structural walls based on the available design information, that is, story weights, wall type, wall length, and wall opening type. Microtremor measurement data of several newly constructed buildings are used to determine unknown model parameters of stiffness estimation function, which minimize the estimation error of eigen frequency. The proposed method can simultaneously estimate the standard stiffness of wall element common to the same specification and the effects of wall opening and wall shape. The validity of the proposed method is examined by using measured actual microtremor records and drawing information of wall types and wall lengths of 19 wooden residential houses.

Using a novel source of quasi-experimental variation in interest rates, we develop a new approach to estimating the Elasticity of Intertemporal Substitution (EIS). In the U.K., the mortgage interest rate features discrete jumps—notches—at thresholds for the loan-to-value (LTV) ratio. These notches generate large bunching below the critical LTV thresholds and missing mass above them. We develop a dynamic model that links these empirical moments to the underlying structural EIS. The average EIS is small, around 0.1, and quite homogeneous in the population. This finding is robust to structural assumptions and can allow for uncertainty, a wide range of risk preferences, portfolio reallocation, liquidity constraints, present bias, and optimization frictions. Our findings have implications for the numerous calibration studies that rely on larger values of the EIS.

Estimating structural models is often viewed as computationally difficult, an impression partly due to a focus on the nested fixed-point (NFXP) approach. We propose a new constrained optimization approach for structural estimation. We show that our approach and the NFXP algorithm solve the same estimation problem, and yield the same estimates. Computationally, our approach can have speed advantages because we do not repeatedly solve the structural equation at each guess of structural parameters. Monte Carlo experiments on the canonical Zurcher bus-repair model demonstrate that the constrained optimization approach can be significantly faster.

How can price elasticities be identified when agents face optimization frictions such as adjustment costs or inattention? I derive bounds on structural price elasticities that are a function of the observed effect of a price change on demand, the size of the price change, and the degree of frictions. The degree of frictions is measured by the utility losses agents tolerate to deviate from the frictionless optimum. The bounds imply that frictions affect intensive margin elasticities much more than extensive margin elasticities. I apply these bounds to the literature on labor supply. The utility costs of ignoring the tax changes used to identify intensive margin labor supply elasticities are typically less than 1% of earnings. As a result, small frictions can explain the differences between micro and macro elasticities, extensive and intensive margin elasticities, and other disparate findings. Pooling estimates from existing studies, I estimate a Hicksian labor supply elasticity of 0.33 on the intensive margin and 0.25 on the extensive margin after accounting for frictions.

Consumers often consider delaying a purchase strategically, anticipating that prices might decrease. Combining two unique data sources from the air-travel industry (posted fare data and booking data), we use a structural model to estimate the fraction of strategic consumers in the population, assuming different levels of sophistication in consumers' perception of future prices: perfect foresight and weak- and strong-form rational expectations. We find that 5.2% to 19.2% of the population is strategic across markets, measured by the first and third quartiles. Our intermarket analysis indicates that shorter trips with more attractive outside options are populated with more strategic consumers. Using a nonparametric approach, we further find that most strategic consumers arrive either at the beginning of the booking horizon or close to departure. Finally, our counterfactual analysis shows that, contrary to conventional wisdom, the presence of strategic consumers does not necessarily hurt revenues. Rather, the impact varies by market. Commitment to a nondecreasing pricing strategy is more likely to benefit business markets than leisure markets, or it could even hurt leisure markets. Intermarket analysis shows that city pairs with lower Internet penetration, higher average price, and shorter distances tend to benefit more from such commitment as well. This paper was accepted by Yossi Aviv, operations management .

We undertake an empirical study of the impact of delay announcements on callers’ abandonment behavior and the performance of a call center with two priority classes. A Cox regression analysis reveals that in this call center, callers’ abandonment behavior is affected by the announcement messages heard. To account for this, we formulate a structural estimation model of callers’ (endogenous) abandonment decisions. In this model, callers are forward-looking utility maximizers and make their abandonment decisions by solving an optimal stopping problem. Each caller receives a reward from service and incurs a linear cost of waiting. The reward and per-period waiting cost constitute the structural parameters that we estimate from the data of callers’ abandonment decisions as well as the announcement messages heard. The call center performance is modeled by a Markovian approximation. The main methodological contribution is the definition of an equilibrium in steady state as one where callers’ expectation of their waiting time, which affects their (rational) abandonment behavior, matches their actual waiting time in the call center, as well as the characterization of such an equilibrium as the solution of a set of nonlinear equations. A counterfactual analysis shows that callers react to longer delay announcements by abandoning earlier, that less patient callers as characterized by their reward and cost parameters react more to delay announcements, and that congestion in the call center at the time of the call affects caller reactions to delay announcements.

We study a model of earnings management and provide predictions about the time-series properties of earnings quality and reporting bias. We estimate the model to empirically separate two components of investor uncertainty: fundamental economic uncertainty, and information asymmetry between the manager and investors due to reporting noise. We find that (1) the null hypothesis of zero reporting bias is rejected; (2) the ratio of the variance of the noise introduced by the reporting process to the variance of earnings shocks is, on average, 45 percent; (3) the reporting noise plays a significantly less prominent role in valuation, due to the persistence of shocks to economic earnings; (4) the magnitude of investors' uncertainty created by reporting noise about firms' assets in place and about future earnings is similar; and (5) ignoring the possibility of reporting distortions would bias the estimates of variance and persistence of economic earnings.

We study customer preference for the bike-share system in the city of London. We estimate a structural demand model on the station network to learn the preference parameters and use the estimated model to provide insights on the design and expansion of the bike-share system. We highlight the importance of network effects in understanding customer demand and evaluating expansion strategies of transportation networks. In the particular example of the London bike-share system, we find that allocating resources to some areas of the station network can be 10 times more beneficial than others in terms of system usage and that the currently implemented station density rule is far from optimal. We develop a new method to deal with the endogeneity problem of the choice set in estimating demand for network products. Our method can be applied to other settings in which the available set of products or services depends on demand. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

We evaluate whether changing from a uniform price (UP) to an increasing block tariff (IBT) changes people's behavior. We exploit a unique setting in which the price scheme moves back and forth yearly from UP to IBT. We discuss the effectiveness of IBT in reducing summer consumption. This issue is relevant to many countries and policymakers interested in designing tariff structures. There is no evidence of how the same consumer may react to systematically switching from one tariff structure to another yearly. We estimate the residential water demand and its price elasticity using a generalized least squared random effect model for the UP and the discrete/continuous choice model for the IBT. In addition, we split the sample between low and high‐consumption groups. For the low consumption group unaffected by the tariff change, the elasticity in the nonsummer months is higher (more elastic) than in the summer. Consumers in this group reduce their elasticity from nonsummer to summer months (−0.299 vs. −0.071, respectively) and increase their consumption by 13%. The high consumption group increased its summer consumption, but only by 8.7%, and contrary to the first group, its elasticity increased significantly (from −0.299 to −0.568). The high‐consumption group is indeed affected by the change in tariff. From a policy perspective, this implies that the IBT structure is relevant. However, if the policy seeks to promote conservation, it needs to be adjusted to a lower decile of the water consumption distribution to affect a more significant portion of the population. Key Points We estimate the residential water demand and its price elasticity under systematic shifts between uniform price and increasing‐block tariff structure We estimate different treatments of the sample: splitting it between summer and nonsummer months and between low and high consumption levels From a policy perspective, we find that people react to tariff changes and that tariff reforms should consider consumers' heterogeneity

Using the intuition that financial markets transfer risks in business time, \"market microstructure invariance\" is defined as the hypotheses that the distributions of risk transfers (\"bets\") and transaction costs are constant across assets when measured per unit of business time. The invariance hypotheses imply that bet size and transaction costs have specific, empirically testable relationships to observable dollar volume and volatility. Portfolio transitions can be viewed as natural experiments for measuring transaction costs, and individual orders can be treated as proxies for bets. Empirical tests based on a data set of 400,000+ portfolio transition orders support the invariance hypotheses. The constants calibrated from structural estimation imply specific predictions for the arrival rate of bets (\"market velocity\"), the distribution of bet sizes, and transaction costs.