Econometric studies for global heating have typically used regional or global temperature averages to study its long memory properties. One typical explanation behind the long memory properties of temperature averages is cross-sectional aggregation. Nonetheless, formal analysis regarding the...

In this paper, we show that a concept of aggregation can hold in large network games with linear best replies. Breaking up large networks into smaller subnetworks, which can be replaced by representative players, leads to a coarse-grained description of strategic interactions. This method of...

We present a model of the time-allocation decision of spouses in order to study the role of heterogeneity in preferences and wages for couples' labor supply. Spouses differ in their tastes for market consumption and non-market goods and activities, and also in their offered or earned wages. They...

This paper used cross-sectional aggregation as the inspiration for a model with long-range dependence that arises in actual data. One of the advantages of our model is that it is less brittle than fractionally integrated processes. In particular, we showed that the antipersistent phenomenon is...

Even the most rudimentary training from Economics 101 starts with demand curves going down and supply curves going up. They are so 'natural' that they sound even more obvious than the Euclidian postulates in mathematics. But are they? What do they actually mean? Start with ''demand curves''. Are...

We compare direct forecasts of HICP and HICP excluding energy and food in the euro area and five member countries to aggregated forecasts of their main components from large Bayesian VARs with a shared set of predictors. We focus on conditional point and density forecasts, in line with...

We estimate a model that allows for dynamic and interdependent responses of morbidity in different local areas to economic conditions at the local and national level, with statistical selection of optimal local area. We apply this approach to quarterly British data on chronic health conditions...

The rate at which workers switch employers without experiencing a spell of unemployment is one of the most important labor market indicators. However, Employer-to-Employer (EE) transitions are hard to measure in widely used matched employer-employee datasets such as those available in the US. We...

The modern Condorcet jury theorem states that under weak conditions, when voters have common interests, elections will aggregate information when the population is large, in any equilibrium. Here, we study the performance of large elections with population uncertainty. We find that the modern...

We provide key insights on expectation formation based on the Bloomberg economic survey: around two thirds of professional forecasters provide GDP forecasts that are temporally consistent, meaning that quarterly forecasts add up to the annual. Temporally consistent forecasts are not more...

We propose a novel copula approach to producing density forecasts of economic aggregates combining models using disaggregate data. Our copula approach is more flexible compared to existing techniques, because it is applicable to any econometric model that produces density forecasts. We construct...

In this paper, we propose a new method to forecast macroeconomic variables that combines two existing approaches to mixed-frequency data in DSGE models. The first existing approach estimates the DSGE model in a quarterly frequency and uses higher frequency auxiliary data only for forecasting...

Researchers and practitioners who use Data Envelopment Analysis often want to incorporate several inputs and outputs in their model to consider as much relevant information as possible. However, too many inputs and outputs can result in the well-known dimensionality problem referred to as the...

This paper documents a comparative application of algorithms to deal with the problem of missing values in higher frequency data sets. We refer to Swiss business tendency survey (BTS) data, in particular the KOF manufacturing surveys, which are conducted in both monthly and quarterly frequency,...

Researchers and practitioners who use Data Envelopment Analysis often want to incorporate several inputs and outputs in their model to consider as much relevant information as possible. However, too many inputs and outputs can result in the well-known dimensionality problem referred to as the...

This paper documents a comparative application of algorithms to deal with the problem of missing values in higher frequency data sets. We refer to Swiss business tendency survey (BTS) data which are conducted in both monthly and quarterly frequency, where an information sub-set is collected at...

We propose several numerical algorithms to compute the distribution of gross loss in a positively dependent catastrophe insurance portfolio. Hierarchical risk aggregation is performed using bivariate copula trees. Six common parametric copula families are studied. At every branching node, the...

Decision-making on real-world problems, including individual process decisions, requires an appropriate and reliable decision support system. Fuzzy set theory, rough set theory, and neutrosophic set theory, which are MCDM techniques, are useful for modeling complex decision-making problems with...

Using new survey data on quantitative growth expectations of firms in Germany, we show that firms resort to local information when forming expectations about aggregate growth. Firms extrapolate from the economic situation in their county, industry growth and their individual business situation....

We exploit the information in the successive vintages of gross domestic expenditure (GDE) and gross domestic income (GDI) from the current comprehensive revision to obtain an improved, timely measure of U.S. aggregate output by exploiting cointegration between the different measures and taking...