English as a Global Language

How far has English already spread? How much further can we expect it to go? In response to the first question, this chapter tries to identify the areas of life where English already serves as a lingua franca in the world (more or less) and those where the language faces sharp competition and does not threaten to marginalize the other major languages. The former areas of life are international safety, the internal business of international organizations, internal communication within the international news industry, international sports and science. The latter areas are the press, television, the internet, publishing and international trade. As to the second question, about the future prospects of English, the chapter argues that the advance of English will depend heavily on the motives to learn the other major languages in the world as well. Based on the empirical evidence, the same model applies to the incentives to learn English and these other languages. On the important topic of welfare, the cultural market is the single one where it is arguable that the progress of English has gone too far. English dominance in the song, the cinema and the best-seller is indeed extraordinary and difficult to reconcile with the evidence popular attachments to home languages, which is otherwise strong and apparent.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

First-and second-best allocations under economic and environmental uncertainty

This paper uses a micro-founded DSGE model to compare second-best optimal environmental policy and the resulting allocation to first-best allocation. The focus is on the source and size of uncertainty, and how this affects optimal choices and the inferiority of second best vis-à-vis first best.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

Competing for Attention: Is the Showiest also the Best?

We introduce attention games. Alternatives ranked by quality (producers, politicians, sexual partners...) desire to be chosen and compete for the imperfect attention of a chooser by investing in their own salience. We prove that if alternatives can control the attention they get, then ”the showiest is the best”: the equilibrium ordering of salience (weakly) reproduces the quality ranking and the best alternative is the one that gets picked most often. This result also holds under more general conditions. However, if those conditions fail, then even the worst alternative can be picked most often.