2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

The European commission

We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency Several types of evidence – including human readings of 12,000 newspaper articles – indicate that our index proxies for movements in policy-related economic uncertainty Our US index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt-ceiling dispute and other major battles over fiscal policy Using firm-level data, we find that policy uncertainty raises stock price volatility and reduces investment and employment in policy-sensitive sectors like defense, healthcare, and infrastructure construction At the macro level, policy uncertainty innovations foreshadow declines in investment, output, and employment in the United States and, in a panel VAR setting, for 12 major economies Extending our US index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upwards since the 1960s

/pdf/measuring-economic-policy-uncertainty-4nrg3ei76f.pdf

Measuring Economic Policy Uncertainty

In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

/pdf/the-theory-of-industrial-organization-19bejph0ej.pdf

The Theory of Industrial Organization

We investigate whether differences in individuals’ experiences of macro-economic shocks affect longterm risk attitudes, as is often suggested for the generation that experienced the Great Depression. Using data from the Survey of Consumer Finances from 1964-2004, we find that birth-cohorts that have experienced high stock market returns throughout their life report lower risk aversion, are more likely to be stock market participants, and, if they participate, invest a higher fraction of liquid wealth in stocks. We also find that cohorts that have experience high inflation are less likely to hold bonds. These results are estimated controlling for age, year effects, and a broad set of household characteristics. Our estimates indicate that stock market returns and inflation early in life affect risk-taking several decades later. However, more recent returns have a stronger effect, which fades away slowly as time progresses. Thus, the experience of risky asset payoffs over the course of an individuals’ life affects subsequent risk-taking. Our results explain, for example, the relatively low rates of stock market participation among young households in the early 1980s (following the disappointing stock market returns in the 1970s depression) and the relatively high participation rates of young investors in the late 1990s (following the boom years in the 1990s).

/pdf/depression-babies-do-macroeconomic-experiences-affect-risk-4iiktg6dri.pdf

Depression Babies: Do Macroeconomic Experiences Affect Risk Taking?*

Recursive multiple-priors

https://economics.yale.edu/sites/default/files/files/Workshops-Seminars/Macroeconomics/piazzesi-031014.pdf

Housing, consumption and asset pricing

When ambiguity-averse investors process news of uncertain quality, they act as if they take a worst-case assessment of quality. As a result, they react more strongly to bad news than to good news. They also dislike assets for which information quality is poor, especially when the underlying fundamentals are volatile. These effects induce ambiguity premia that depend on idiosyncratic risk in fundamentals as well as skewness in returns. Moreover, shocks to information quality can have persistent negative effects on prices even if fundamentals do not change. FINANCIAL MARKET PARTICIPANTS ABSORB a large amount of news, or signals, every day. Processing a signal involves quality judgments: News from a reliable source should lead to more portfolio rebalancing than news from an obscure source. Unfortunately, judging quality itself is sometimes difficult. For example, stock picks from an unknown newsletter without a track record might be very reliable or entirely useless—it is simply hard to tell. Of course, the situation is different when investors can draw on a lot of experience that helps them interpret signals. This is true especially for “tangible” information, such as earnings reports, that lends itself to quantitative analysis. By looking at past data, investors may become quite confident about how well earnings forecast returns. This paper focuses on information processing when there is incomplete knowledge about signal quality. The main idea is that, when quality is difficult to judge, investors treat signals as ambiguous. They do not update beliefs in standard Bayesian fashion, but behave as if they have multiple likelihoods in mind when processing signals. To be concrete, suppose that θ is a parameter that an investor wants to learn. We assume that a signal s is related to the parameter by a family of likelihoods: s = θ + � , � ∼ N � 0, σ 2 s � , σ 2 s ∈ � σ 2

/pdf/ambiguity-information-quality-and-asset-pricing-1kwget89es.pdf

Ambiguity, Information Quality, and Asset Pricing

This study quantitatively assesses the effects of inflation through changes in the value of nominal assets. It documents nominal asset positions in the United States across sectors and groups of households and estimates the wealth redistribution caused by a moderate inflation episode. The main losers from inflation are rich, old households, the major bondholders in the economy. The main winners are young, middle‐class households with fixed‐rate mortgage debt. Besides transferring resources from the old to the young, inflation is a boon for the government and a tax on foreigners. Lately, the amount of U.S. nominal assets held by foreigners has grown dramatically, increasing the potential for a large inflation‐induced wealth transfer from foreigners to domestic households.

/pdf/inflation-and-the-redistribution-of-nominal-wealth-2lbkgrnwa6.pdf

Inflation and the Redistribution of Nominal Wealth

Several recent twin' currency and banking crises were preceded by lending booms during which the banking system financed rapid growth of the nontradable (N) sector by borrowing in foreign currency. They were followed by recessions during which a sharp decline in credit especially hurt the N-sector. This paper presents a model that accounts for these stylized facts. A crucial element is that we model a banking system that is simultaneously subject to two distortions typical of international credit markets: bailout guarantees and the imperfect enforceability of contracts. The interaction of these distortions produces unusually fast N-sector growth, together with a real appreciation, during the boom. However, it is also responsible for self-fulfilling twin crises, which have persistent adverse effects on N-sector output.

Martin Schneider

Papers

Recursive multiple-priors

Housing, consumption and asset pricing

Ambiguity, Information Quality, and Asset Pricing

Inflation and the Redistribution of Nominal Wealth

Balance Sheet Effects, Bailout Guarantees and Financial Crises