A importância de um índice de volatilidade para o mercado brasileiro

Este trabalho objetiva analisar a importância de um índice de volatilidade implícita para o mercado brasileiro. Por ser conhecida como uma medida das expectativas futuras dos investidores, diversos estudos, principalmente na literatura estrangeira, tem consegui extrair importantes informações quanto às mudanças na volatilidade implícita com a chegada de novos dados sobre a economia. Analisando as opções de juros (IDI) e de dólar, este trabalho verifica que informações de dados macroeconômicos impactam a volatilidade. Os resultados demonstram que as expectativas quanto ao mercado de juros são impactadas por diversos dados, porém o mesmo não acontece com o mercado de dólar, a qual se demonstrou ser impactada somente por intervenções do Banco Central via colocação de swaps. Por fim, o trabalho conclui que existem varáveis não transacionáveis que explicam as variações na volatilidade implícita, mostrando que as volatilidades implícitas das opções possuem bastantes informações quanto às expectativas.

Estudo comparativo do poder preditivo do PIB brasileiro por variáveis macroeconômicas em relação ao conjunto de variáveis da estrutura de taxa de juros

O trabalho busca comparar dois conjuntos de informações para a projeção das variações do PIB brasileiro: através de modelos econométricos aplicados sobre a série univariada do PIB, e a aplicação dos mesmos modelos, mas contemplando adicionalmente o conjunto de informação com dados da estrutura a termo de taxa de juros de swap PRÉ-DI. O objetivo é verificar, assim como descrito na literatura internacional, se informações de variáveis financeiras tem a capacidade de incrementar o poder preditivo de projeções de variáveis macroeconômicas, na medida em que esses dados também embutem as expectativas dos agentes em relação ao desenvolvimento do cenário econômico. Adicionalmente, o mesmo procedimento aplicado para os dados brasileiros é aplicado sobre as informações dos Estados Unidos, buscando poder fornecer ao estudo uma base de comparação sobre os dados, tamanho da amostra e estágio de maturidade das respectivas economias. Como conclusão do resultado do trabalho está o fato de que foi possível obter um modelo no qual a inclusão do componente de mercado apresenta menores erros de projeção do que as projeções apenas univariadas, no entanto, os ganhos de projeção não demonstram grande vantagem comparativa a ponto de poder capturar o efeito de antecipação do mercado em relação ao indicador econômico como em alguns casos norte-americanos. Adicionalmente o estudo demonstra que para este trabalho e amostra de dados, mesmo diante de diferentes modelos econométricos de previsão, as projeções univariadas apresentaram resultados similares.

Inflation persistence and flexible prices

The inability of rational expectation models with money supply rules to deliver inflation persistence following a transitory deviation of money growth from trend is due to the rapid adjustment of the price level to expected events. The observation of persistent inflation in macroeconomic data leads many economists to believe that prices adjust sluggishly and/or expectations must not be rational. Inflation persistence in U.S. data can be characterized by a vector autocorrelation function relating inflation and deviations of output from trend. In the vector autocorrelation function both inflation and output are highly persistent and there are significant positive dynamic cross-correlations relating inflation and output. This paper shows that a flexible-price general equilibrium business cycle model with money and a central bank using a Taylor rule can account for these patterns. There are no sticky prices and no liquidity effects. Agents decisions in a period are taken only after all shocks are observed. The monetary policy rule transforms output persistence into inflation persistence and creates positive cross-correlations between inflation and output.

The employment situation in Latin America and the Caribbean: Crisis, stabilization and reactivation: performance of the labour market in 2009

Following a five-year period during which economic and social performance in Latin America and the Caribbean surpassed anything seen in recent decades, the global economic and financial crisis not only hurt macroeconomic variables but also impacted heavily on labour markets in the region’s countries. Between 2003 and 2008 employment rates had risen considerably, especially in the formal sector, but the crisis spelled a reversal of this trend. Nevertheless, the region was better prepared than it had been in previous crises, since it had achieved a sound fiscal footing, a good level of international reserves and low rates of inflation. This meant that the authorities had the space to implement countercyclical policies on both fiscal and monetary levels. Be this as it may, faced with the worst global crisis since the Great Depression of the 1930s, these measures could only attenuate the impact on the region’s economies —they could not prevent it altogether. Furthermore, the crisis struck with notable differences among subregions and countries depending on the nature of their trade integration, and not all the countries had the fiscal space to implement vigorous countercyclical policies. As discussed in this third ECLAC/ILO bulletin, the crisis did less damage to the region’s labour markets than had been feared at the beginning of last year, thanks to the implementation of public policies geared towards employment, as reviewed in the two previous bulletins. This bulletin offers an additional analysis from the perspective of gender equality. Moreover, some countries in the region, notably Brazil, managed to rapidly stabilize and revive economic growth, with positive effects on labour variables. The fact remains, however, that millions in Latin America and the Caribbean lost their jobs or were obliged to accept more poorly paid employment in more precarious conditions. The macroeconomic data indicate that recovery is under way and is stronger and occurring more rapidly than foreseen one year ago. In fact, regional growth in 2010 may well exceed the 4.1% forecast at the end of 2009. Consequently, although the unemployment rate may be expected to record a modest drop, it may not return to pre-crisis levels. The upturn is taking many different forms in the countries of the region. In some, especially in South America, recovery has benefited from the buoyancy of the Asian economies, whose demand for natural resources has driven large increases in exports, in terms of both volume and price. Countries whose economies are closely tied to the United States economy are benefiting from the recovery there, albeit more slowly and with a certain lag. Conversely, some countries are still suffering from major disequilibria, which are hampering their economic reactivation. Lastly, Chile and Haiti were both victims of devastating earthquakes early in the year and are therefore facing additional challenges associated with reconstruction, on top of their efforts to sustain an economic upturn. Despite the relatively favourable outlook for regional growth in 2010, great uncertainty still surrounds the global economy’s recovery, which affects the region’s economic prospects over the longer term. The weakness of the recovery in some regions and the doubts about its sustainability in others, as well as shocks that have occurred in international financial markets, are warning signs which authorities need to monitor continuously because of the region’s close integration with the global economy. In addition, a return to growth does not directly or automatically mean higher employment rates —still less decent working conditions. Although some labour indicators have performed reasonably favourably since the end of last year, the countries still face daunting challenges in improving the labour market integration of millions in Latin America and the Caribbean who are not seeing the fruits of renewed growth. This is why it is important to learn the lessons arising from the policies implemented during the crisis to offset its impact on labour markets. With this third joint bulletin, ECLAC and ILO continue to pursue their objective of affording the region the information and analyses needed to face these challenges, as regards both trends in the region’s labour markets and the corresponding policy options.

Home ownership, labour markets and the economic crisis. ECRI Commentary No. 14, 15 June 2015

In recent decades, a growing body of academic literature has focused on the possible negative effects of high levels of home ownership, especially on labour markets. Morethan-optimal levels of home ownership may impede the mobility of workers, resulting in higher unemployment rates in some European regions. Against that backdrop, a simple model was devised to test the relationship between home ownership, mobility and unemployment. Recent macroeconomic data published by Eurostat suggest that both the variables of mobility and home ownership have had a significant impact on the dynamics of unemployment rates across the EU28.

Macroeconomic forecasting with mixed-frequency data: forecasting output growth in the United States

Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth, and that MIDAS is an effective way to exploit monthly data compared with alternative methods.

Macroeconomic announcements, price discovery, and order flow efects in the stock market: evidence from incomplete data and multiple financial markets

This paper investigates heterogeneity in the market assessment of public macro- economic announcements by exploring (jointly) two main mechanisms through which macroeconomic news might enter stock prices: instantaneous fundamental news im- pacts consistent with the asset pricing view of symmetric information, and permanent order ow e¤ects consistent with a microstructure view of asymmetric information related to heterogeneous interpretation of public news. Theoretical motivation and empirical evidence for the operation of both mechanisms are presented. Signi cant in- stantaneous news impacts are detected for news related to real activity (including em- ployment), investment, in ation, and monetary policy; however, signi cant order ow e¤ects are also observed on employment announcement days. A multi-market analysis suggests that these asymmetric information e¤ects come from uncertainty about long term interest rates due to heterogeneous assessments of future Fed responses to em- ployment shocks.

Labor force data needs for macroeconomic planning and projects /

Mode of access: Internet.

Making a match: Combining theory and evidence in policy-oriented macroeconomic modeling

A persistent question in the development of models for macroeconomic policy analysis has been the relative role of economic theory and evidence in their construction. This paper looks at some popular strategies that involve setting up a theoretical or conceptual model (CM) which is transformed to match the data and then made operational for policy analysis. A dynamic general equilibrium model is constructed that is similar to standard CMs. After calibration to UK data it is used to examine the utility of formal econometric methods in assessing the match of the CM to the data and also to evaluate some standard model-building strategies. Keywords: Policy oriented economic modeling; Model evaluation; VAR models

Intraday Seasonalities and Macroeconomic News Announcements

Using a data set consisting of three years of 5-minute intraday stock index returns for major European stock indices and U.S. macroeconomic surprises, the conditional mean and volatility behaviors in European market were investigated. The findings suggested that the opening of the U.S market significantly raised the level of volatility in Europe, and that all markets respond in an identical fashion. Furthermore, the U.S. macroeconomic surprises exerted an immediate and major impact on both European stock markets’ returns and volatilities. Thus, high frequency data appear to be critical for the identification of news that impacted the markets.

Monetary Policy, Stock Price Misalignments and Macroeconomic Instability

Perhaps the most fundamental prediction of financial theory is that the expected returns on financial assets are determined by the amount of risk contained in their payoffs. Assets with a riskier payoff pattern should provide higher expected returns than assets that are otherwise similar but provide payoffs that contain less risk. Financial theory also predicts that not all types of risks should be compensated with higher expected returns. It is well-known that the asset-specific risk can be diversified away, whereas the systematic component of risk that affects all assets remains even in large portfolios. Thus, the asset-specific risk that the investor can easily get rid of by diversification should not lead to higher expected returns, and only the shared movement of individual asset returns – the sensitivity of these assets to a set of systematic risk factors – should matter for asset pricing. It is within this framework that this thesis is situated. The first essay proposes a new systematic risk factor, hypothesized to be correlated with changes in investor risk aversion, which manages to explain a large fraction of the return variation in the cross-section of stock returns. The second and third essays investigate the pricing of asset-specific risk, uncorrelated with commonly used risk factors, in the cross-section of stock returns. The three essays mentioned above use stock market data from the U.S. The fourth essay presents a new total return stock market index for the Finnish stock market beginning from the opening of the Helsinki Stock Exchange in 1912 and ending in 1969 when other total return indices become available. Because a total return stock market index for the period prior to 1970 has not been available before, academics and stock market participants have not known the historical return that stock market investors in Finland could have achieved on their investments. The new stock market index presented in essay 4 makes it possible, for the first time, to calculate the historical average return on the Finnish stock market and to conduct further studies that require long time-series of data.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

ARE OECD MACROECONOMIC VARIABLES TREND STATIONARY? EVIDENCE FROM PANEL STATIONARITY TESTS ALLOWING FOR A STRUCTURAL BREAK AND CROSS-SECTIONAL DEPENDENCE

This article applies the panel stationarity test with a break proposed by Hadri and Rao (2008) to examine whether 14 macroeconomic variables of OECD countries can be best represented as random walk or stationary fluctuations around a deterministic trend. In contrast to previous studies, based essentially on visual inspection of the break type or just applying the most general break model, we use a model selection procedure based on BIC. We do this for each time series so that heterogeneous break models are allowed for in the panel. Our results suggest, overwhelmingly, that if we account for a structural break, cross-sectional dependence and choose the break models to be congruent with the data, then the null of stationarity cannot be rejected for all the 14 macroeconomic variables examined in this article. This is in sharp contrast with the results obtained by Hurlin (2004), using the same data but a different methodology.

Order Flow and the Monetary Model of Exchange Rates: Evidence from a Novel Data Set

We propose an exchange rate model that is a hybrid of the conventional specification with monetary fundamentals and the Evans–Lyons microstructure approach. We estimate a model augmented with order flow variables, using a unique data set: almost 100 monthly observations on interdealer order flow on dollar/euro and dollar/yen. The augmented macroeconomic, or “hybrid,” model exhibits greater in-sample stability and out of sample forecasting improvement vis-à-vis the basic macroeconomic and random walk specifications.

Macroeconomic information, structural change, and the prediction of fiscal aggregates

Previous research on the prediction of fiscal aggregates has shown evidence that simple autoregressive models often provide better forecasts of fiscal variables than multivariate specifications. We argue that the multivariate models considered by previous studies are small-scale, probably burdened by overparameterization, and not robust to structural changes. Bayesian Vector Autoregressions (BVARs), on the other hand, allow the information contained in a large data set to be summarized efficiently, and can also allow for time variation in both the coefficients and the volatilities. In this paper we explore the performance of BVARs with constant and drifting coefficients for forecasting key fiscal variables such as government revenues, expenditures, and interest payments on the outstanding debt. We focus on both point and density forecasting, as assessments of a country’s fiscal stability and overall credit risk should typically be based on the specification of a whole probability distribution for the future state of the economy. Using data from the US and the largest European countries, we show that both the adoption of a large system and the introduction of time variation help in forecasting, with the former playing a relatively more important role in point forecasting, and the latter being more important for density forecasting.