In this paper we study inference for a conditional model with a jump in the conditional density, where the location and size of the jump are described by regression lines. This interesting structure is shared by several structural econometric models. Two prominent examples are the standard...

In this paper we study estimation and inference in structural models with a jump in the conditional density, where the location and size of the jump are described by regression lines. Two prominent examples are auction models, where the density jumps from zero to a positive value, and the...

This paper develops a theory of high and low (extremal) quantile regression: the linear models, estimation, and inference. In particular, the models coherently combine the convenient, flexible linearity with the extreme-value-theoretic restrictions on tails and the general heteroscedasticity...

This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

Several sales models for a consumer’s goods manufacturer firm are developed and tested. A data panel approach is used to model aggregate sales across three countries, using mainly price and trade investment. We show how useful can be different panel data models to forecast sales across...

Mathematical Economics is closely related with Social Choice Theory. In this paper, an attempt has been made to show this relation by introducing utility functions, preference relations and Arrow’s impossibility theorem with easier mathematical calculations. The paper begins with some...

This paper examines how data-driven personalized decisions can be made while preserving consumer privacy. Our setting is one in which the firm chooses a personalized price based on each new customer's vector of individual features; the true set of individual demand-generating parameters is...

We show FC-MNL is flexible in the sense of Diewert (1974), thus its parameters can be chosen to match a well-defined class of possible own- and cross-price elasticities of demand. In contrast to models such as Probit and Random Coefficient-MNL models, FC-MNL does not require estimation via...

The role of customer value has been largely recognized over time by the firms as an instrument towards stimulating market share and profit optimization. The customer values for innovative products and unfamiliar brands of firm in competitive markets are determined largely by habits,...