Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

It is well known that cointegration between the level of two variables (e.g. prices and dividends) is a necessary condition to assess the empirical validity of a present-value model (PVM) linking them. The work on cointegration,namelyon long-run co-movements, has been so prevalent that it is often over-looked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. This amounts to investigate whether short-run co-movememts steming from common cyclical feature restrictions are also present in such a system. In this paper we test for the presence of such co-movement on long- and short-term interest rates and on price and dividend for the U.S. economy. We focuss on the potential improvement in forecasting accuracies when imposing those two types of restrictions coming from economic theory.

Automatic model selection for forecasting brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We nd that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.

Automatic model selection for forecasting Brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We find that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.

An assessment of the economic impact of climate change on the Agriculture, Health and Tourism sectors in Saint Lucia

This report analyses the agriculture, health and tourism sectors in Saint Lucia to assess the potential economic impacts of climate change on the sectors. The fundamental aim of this report is to assist with the development of strategies to deal with the potential impact of climate change in Saint Lucia. It also has the potential to provide essential input for identifying and preparing policies and strategies to help advance the Caribbean subregion closer to solving problems associated with climate change and attaining individual and regional sustainable development goals. Some of the key anticipated impacts of climate change for the Caribbean include elevated air and sea-surface temperatures, sea-level rise, possible changes in extreme events and a reduction in freshwater resources. The economic impact of climate change on the three sectors was estimated for the A2 and B2 IPCC scenarios until 2050. An evaluation of various adaptation strategies for each sector was also undertaken using standard evaluation techniques. The key subsectors in agriculture are expected to have mixed impacts under the A2 and B2 scenarios. Banana, fisheries and root crop outputs are expected to fall with climate change, but tree crop and vegetable production are expected to rise. In aggregate, in every decade up to 2050, these sub-sectors combined are expected to experience a gain under climate change with the highest gains under A2. By 2050, the cumulative gain under A2 is calculated as approximately US$389.35 million and approximately US$310.58 million under B2, which represents 17.93% and 14.30% of the 2008 GDP respectively. This result was unexpected and may well be attributed to the unavailability of annual data that would have informed a more robust assessment. Additionally, costs to the agriculture sector due to tropical cyclones were estimated to be $6.9 million and $6.2 million under the A2 and B2 scenarios, respectively. There are a number of possible adaptation strategies that can be employed by the agriculture sector. The most attractive adaptation options, based on the benefit-cost ratio are: (1) Designing and implementation of holistic water management plans (2) Establishment of systems of food storage and (3) Establishment of early warning systems. Government policy should focus on the development of these adaption options where they are not currently being pursued and strengthen those that have already been initiated, such as the mainstreaming of climate change issues in agricultural policy. The analysis of the health sector placed focus on gastroenteritis, schistosomiasis, ciguatera poisoning, meningococal meningitis, cardiovascular diseases, respiratory diseases and malnutrition. The results obtained for the A2 and B2 scenarios demonstrate the potential for climate change to add a substantial burden to the health system in the future, a factor that will further compound the country’s vulnerability to other anticipated impacts of climate change. Specifically, it was determined that the overall Value of Statistical Lives impacts were higher under the A2 scenario than the B2 scenario. A number of adaptation cost assumptions were employed to determine the damage cost estimates using benefit-cost analysis. The benefit-cost analysis suggests that expenditure on monitoring and information provision would be a highly efficient step in managing climate change and subsequent increases in disease incidence. Various locations in the world have developed forecasting systems for dengue fever and other vector-borne diseases that could be mirrored and implemented. Combining such macro-level policies with inexpensive micro-level behavioural changes may have the potential for pre-empting the re-establishment of dengue fever and other vector-borne epidemic cycles in Saint Lucia. Although temperature has the probability of generating significant excess mortality for cardiovascular and respiratory diseases, the power of temperature to increase mortality largely depends on the education of the population about the harmful effects of increasing temperatures and on the existing incidence of these two diseases. For these diseases it is also suggested that a mix of macro-level efforts and micro-level behavioural changes can be employed to relieve at least part of the threat that climate change poses to human health. The same principle applies for water and food-borne diseases, with the improvement of sanitation infrastructure complementing the strengthening of individual hygiene habits. The results regarding the tourism sector imply that the tourism climatic index was likely to experience a significant downward shift in Saint Lucia under the A2 as well as the B2 scenario, indicative of deterioration in the suitability of the island for tourism. It is estimated that this shift in tourism features could cost Saint Lucia about 5 times the 2009 GDP over a 40-year horizon. In addition to changes in climatic suitability for tourism, climate change is also likely to have important supply-side effects on species, ecosystems and landscapes. Two broad areas are: (1) coral reefs, due to their intimate link to tourism, and, (2) land loss, as most hotels tend to lie along the coastline. The damage related to coral reefs was estimated at US$3.4 billion (3.6 times GDP in 2009) under the A2 scenario and US$1.7 billion (1.6 times GDP in 2009) under the B2 scenario. The damage due to land loss arising from sea level rise was estimated at US$3.5 billion (3.7 times GDP) under the A2 scenario and US$3.2 billion (3.4 times GDP) under the B2 scenario. Given the potential for significant damage to the industry a large number of potential adaptation measures were considered. Out of these a short-list of 9 potential options were selected by applying 10 evaluation criteria. Using benefit-cost analyses 3 options with positive ratios were put forward: (1) increased recommended design speeds for new tourism-related structures; (2) enhanced reef monitoring systems to provide early warning alerts of bleaching events, and, (3) deployment of artificial reefs or other fish-aggregating devices. While these options had positive benefit-cost ratios, other options were also recommended based on their non-tangible benefits. These include the employment of an irrigation network that allows for the recycling of waste water, development of national evacuation and rescue plans, providing retraining for displaced tourism workers and the revision of policies related to financing national tourism offices to accommodate the new climate realities.

Analysis and developments of uncertainty processors for real time flood forecasting

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

Myanmar's non-resource export potential after the lifting of economic sanctions : a gravity model analysis

Easing of economic sanctions by Western countries in 2012 augmented the prospect that Myanmar will expand its exports. On the other hand, a sharp rise in natural resource exports during the sanctions brings in a concern about the "Dutch disease". This study projects Myanmar's export potential by calculating counterfactual export values with an augmented gravity model that takes into account the effects of natural resource exports on non-resource exports. Without taking into account the effects of natural resource exports, the counterfactual predicted values of non-resource exports during 2004–2011 are more than five times larger than the actual exports. If we take into account the effects, however, the predicted values are smaller than the actual exports. The empirical results imply that the "Dutch disease" is at stake in Myanmar than any other Southeast Asian countries.

The emission reduction effect and economic impact of an energy tax vs. a carbon tax in China : a dynamic CGE model analysis

Chinese government commits to reach its peak carbon emissions before 2030, which requires China to implement new policies. Using a CGE model, this study conducts simulation studies on the functions of an energy tax and a carbon tax and analyzes their effects on macro-economic indices. The Chinese economy is affected at an acceptable level by the two taxes. GDP will lose less than 0.8% with a carbon tax of 100, 50, or 10 RMB/ton CO2 or 5% of the delivery price of an energy tax. Thus, the loss of real disposable personal income is smaller. Compared with implementing a single tax, a combined carbon and energy tax induces more emission reductions with relatively smaller economic costs. With these taxes, the domestic competitiveness of energy intensive industries is improved. Additionally, we found that the sooner such taxes are launched, the smaller the economic costs and the more significant the achieved emission reductions.

Forecasting migration between the EU, V4 and Eastern Europe. Impact of visa abolition. OSW Report, July 2014

This book is the result of one year of solid work among a multinational research team assembled from seven states (Poland, Czechia, Hungary, Slovakia, Ukraine, Belarus and Moldova). It aims at a detailed analysis of migration patterns and migration forecasts from Ukraine, Belarus and Moldova to the EU/V4. In particular, the nexus between EU visa policy and migration dynamics as well as the impact of economic, political and institutional factors on migration from Eastern Europe have been investigated. The importance of migration policy must be stressed here. Together with demand for the foreign labour force (labour market needs, level of wages, existing work opportunities) and migration networks (including ethnic links), migration policy has a powerful influence on the scale, directions and characteristics of human flows.

Election Forecasting under Opaque Conditions

Election forecasting models assume retrospective economic voting and clear mechanisms of accountability. Previous research indeed indicates that incumbent political parties are being held accountable for the state of the economy. In this article we develop a ‘hard case’ for the assumptions of election forecasting models. Belgium is a multiparty system with perennial coalition governments. Furthermore, Belgium has two completely segregated party systems (Dutch and French language). Since the prime minister during the period 1974-2011 has always been a Dutch language politician, French language voters could not even vote for the prime minister, so this cognitive shortcut to establish political accountability is not available. Results of an analysis for the French speaking parties (1981-2010) show that even in these conditions of opaque accountability, retrospective economic voting occurs as election results respond to indicators with regard to GDP and unemployment levels. Party membership figures can be used to model the popularity function in election forecasting.

Forecasting trade and the merchant fleet. Final report.

Maritime Administration, Washington, D.C.

Cost and economic impact of tire reserve load requirements. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Energy and economic impacts of projected freight transportation improvements. Final report.

Transportation Systems Center, Cambridge, Mass.

Economic forecast report /

"February 2010."

Economic outlook & forecast /

Copyrighted in 2008 by Moody's Analytics.