Under the condition of the finite sample or the unknown distributed error term, testing for spatial dependence in panel data models is an unresolved problem in spatial econometrics. In this paper, a fast double bootstrap (FDB) method is used to construct bootstrap Moran's I tests for Moran's I...

Over the last three decades, China's product, labor, and capital markets have become gradually more integrated within its borders, although integration has been significantly slower for capital markets. There remains a significant urban-rural divide, and Chinese cities tend to be under-sized by...

This paper studies markets, such as Internet marketplaces for used cars or mortgages, in which consumers engage in sequential search. In particular, we consider the impact of information-brokers (experts) who can, for a fee, provide better information on true values of opportunities. We...

A problem that often arises in the process of searching for a job or for a candidate to fill a position is that applicants do not know if they will receive an offer from any given firm with which they interview, and, conversely, firms do not know whether applicants will definitely take positions...

Ensuring sufficient liquidity is one of the key challenges for designers of prediction markets. Various market making algorithms have been proposed in the literature and deployed in practice, but there has been little effort to evaluate their benefits and disadvantages in a systematic manner. We...

This paper develops a model of a learning market-maker by extending the Glosten-Milgrom model of dealer markets. The market-maker tracks the changing true value of a stock in settings with informed traders (with noisy signals) and liquidity traders, and sets bid and ask prices based on its...

Pandemics can cause immense disruption and damage to communities and societies. Thus far, modeling of pandemics has focused on either large-scale differential equation models like the SIR and the SEIR models, or detailed micro-level simulations, which are harder to apply at a global scale. This...

We present a new methodology for estimating time-varying conditional skewness. Our model allows for changing means and variances, uses a maximum likelihood framework with instruments, and assumes a non-central <italic>t</italic> distribution. We apply this method to daily, weekly, and monthly stock returns, and...

The recent U.S. financial crisis and governmental bailout of financial institutions have intensified the debate on the need for effectively measuring and monitoring the financial institutions’ risks. This paper contributes to this discussion by introducing a market-based capital measurement...

In this paper, we study predictability of exchange rates and explore determinants of its dynamics over time. We model the admissible amount of predictability in two ways, each corresponding in a stylized manner to a broad class of rational currency pricing models, namely those under which the...