Prices, Profits, Proxies, and Production

This paper studies nonparametric identification and counterfactual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities and prices are latent rendering standard approaches inapplicable. Instead, we require observation of profits or other optimizing-values such as costs or revenues, and either prices or price proxies of flexibly chosen variables. We extend classical duality results for price-taking firms to a setup with discrete heterogeneity, endogeneity, and limited variation in possibly latent prices. Finally, we show that convergence results for nonparametric estimators may be directly converted to convergence results for production sets.Comment: This paper was previously circulated with the title "Prices, Profits, and Production

2022-8 Slutsky Matrix Symmetry: A New Behavioral Condition

The Slutsky matrix function encodes all the information about local variations in demand with respect to small (Slutsky) compensated price changes. When the demand function is the result of utility maximization the Slutsky matrix is symmetric. However, symmetry does not imply rationality. Here, we provide a necessary and sufficient condition for Slutsky symmetry. The new condition requires symmetric attention to compensated price-paths

Oil Spill Modeling in Sea Ice Covered Ocean

The ongoing reduction in extent and thickness of sea ice in the Arctic allows the expansion of shipping activity and oil exploration in the high north, and with that a potential increased risk of oil spill in ice covered areas. This thesis asses the response of two oil-in-ice surface drift models implemented in an open-source Lagrangian framework and forced by four dif- ferent ice-ocean products (RIOPS, TOPAZ4 real-time forecast system, TOPAZ4 reanalysis and SVIM). Both approaches were evaluated over three sets of simulations: (I) a field experiment conducted in the Barents Sea marginal ice zone in 2009; (II) observed trajectories of buoys in the ice pack and in the Barents Sea marginal ice zone; and (III) stochastic simulations (960 runs, from 1998 to 2017) to reproduce a hypothetical oil spill in the Kara Sea. Results from experiments (I) and (II) indicate that the two drift models provide similar response both in the ice pack and the marginal ice zone under the same forcing. It was also found that finer horizontal resolution ice-ocean products (RIOPS and SVIM) did not reproduce better the ob- served drifts. The experiment (III) revealed that the sea ice concentration (%) field dictates the spread, the predominant direction of trajectories and the distance (km) traveled by the cloud of particles (SVIM: -1.41 km/% and TOPAZ4 reanalysis: -1.24 km/%).Master's Thesis in Meteorology and OceanographyGEOF399MAMN-GEO

2020-2 Prices, Profits, Proxies, and Production

Abstract This paper studies nonparametric identification and counterfactual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities and prices are latent rendering standard approaches inapplicable. Instead, we require observation of profits or other optimizing-values such as costs or revenues, and either prices or price proxies of flexibly chosen variables. We extend classical duality results for price-taking firms to a setup with discrete heterogeneity, endogeneity, and limited variation in possibly latent prices. Finally, we show that convergence results for nonparametric estimators may be directly converted to convergence results for production sets

2022-9 A Rationalization of the Weak Axiom of Revealed Preference

Samuelson’s (1938) weak (generalized) axiom of revealed preference– WGARP–is a minimal and appealing consistency condition of choice. We offer a rationalization of WGARP in general settings. Our main result is an exact analog of the celebrated Afriat’s theorem, but for WGARP. Its ordinal rationalization is in terms of an asymmetric and locally nonsatiated preference function. Its cardinal rationalization uses a coalitional multi-utility (CMU) maxmin representation with a coherency restriction on the coalition structure. Effectively, the CMU representation aggregates piecemeal preferences within the decision maker (multiple rationales without preference reversals that allow for transitivity violations). Basic consumer theory and welfare analysis are also developed. Extensions to the weak axiom of revealed preference–WARP–and choices obeying the law of demand are included

2022-6 Prices, Profits, Proxies, and Production

This paper studies nonparametric identification and counterfactual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities and prices are latent, rendering standard approaches inapplicable. Instead, we require observation of profits or other optimizing-values such as costs or revenues, and either prices or price proxies of flexibly chosen variables. We extend classical duality results for price-taking firms to a setup with discrete heterogeneity, endogeneity, and limited variation in possibly latent prices. Finally, we show that convergence results for nonparametric estimators may be directly converted to convergence results for production sets

2023-2 Dynamic and Stochastic Rational Behavior

We analyze consumer demand behavior using Dynamic Random Utility Model (DRUM). Under DRUM, a consumer draws a utility function from a stochastic utility process in each period and maximizes this utility subject to her budget constraint. DRUM allows unrestricted time correlation and cross-section heterogeneity in preferences. We fully characterize DRUM for a panel data of consumer choices and budgets. DRUM is linked to a finite mixture of deterministic behavior represented as the Kronecker product of static rationalizable behavior. We provide a generalization of the Weyl-Minkowski theorem that uses this link and enables conversion of the characterizations of the static Random Utility Model (RUM) of McFadden-Richter (1990) to its dynamic form. DRUM is more flexible than Afriat’s (1967) framework for time series and more informative than RUM. We show the feasibility of the statistical test of DRUM in a Monte Carlo study