Top PDF HOUSING MARKETS IN SELECTED EUROPEAN COUNTRIES AND THE USA

mortgage debt in relation to GDP and inflation and the level of interest rates on mortgage loans, is of primary importance for the changes taking place in housing markets. The evaluation of changes occurring in domestic housing markets should be based on the identification of such structural characteristics as: the volume of the housing stock, the number of ready-to-use flats, the number of issued building permits, the indices of housing prices, and the number of trans- actions concerning purchase of flats or houses. Due to the specificity and local nature of the real estate market and the influence of macroeconomic factors, we should assume that there are considerable differences in the development of real estate markets in particular countries. The presentation of the changes taking place in housing markets in selected European countries and the USA is the aim of this article. The basic research period covers the years 1998-2009, but wherever the availability of data allowed so, we covered with our research the years 1963-2010.

of the Millennium Development Goals (MDG), the focus of one of the world’s largest international organization was placed on existential issues related to the survival of the environment and addressing the basic needs of every human being (United Nations General Assembly 2000). The Sustainable Development Goals (SDG) take us a significant step further by not only ensuring what humanity needs to survive, but securing goals that are necessary in order for humanity to prosper. By analysing the SDGs it is clearly possible to state that one of their key guidelines is improving and increasing human capital (United Nations 2015). Many of the goals, such as achieving full employment, are standard topics of academic debates, yet whether such a concept can be achieved has often been contested (Seccareccia 2015). Several authors have addressed the mind-set change concerning the SDGs as primarily human centred and answering key issues humanity is facing today (Kumar, Kuman, and Vivekadhish 2016). There are several methodological approaches to measuring human capital 2 and while there are

This paper looks exclusively at day of the week effects and month of the year effects, in European stock markets. It makes several contributions to the literature on calendar effects in stock market returns. First, we discuss the shortcomings of previously used models for the detection of calendar effects, and we propose a simpler model specification that overcomes those shortcomings. Second, we recognize non-normality and autocorrelation in stock market returns, and time-dependent variance of the residuals of linear regressions, and apply appropriate statistical methodologies to tackle these problems, including the bootstrap approach and the GARCH model, adding statistical robustness to our results. Third, we examine the time-stability of the most significant calendar effects in the period under study. Fourth, we use observations from a set of seventeen countries of the same economic region, allowing us to conclude if calendar effects are across-the-board effects in that region or only country-specific effects. This is important to know, because some possible explanations for calendar effects, like psychological traits of investors, would imply across-the-board effects, while other explanations, like those related to fiscal motivations or market structure, allow for country-specific calendar effects. Five, we use data from recent years, from 1994 to 2007, on West and Central European stock markets, thus adding and updating international evidence on calendar effects.

Accession of these CEEC in the EU brought about significant price increases only for beef, sugar, milk and milk products and coarse grains (barley, maize and rye) 13 . Also, the enlargement of the EU in 2004 brought price increases for cereals. Production of wheat rose from 2004 in the CEEC, wheat prices are expected to remain competitive on world markets so eventual surpluses could be exported without export subsidies. According to different studies of European Commission, surpluses are likely result for rye. Increased feed requirements are predicted to absorb higher maize production, while developments on the barley market are likely to depend on exchange rate movements. The production of beef has increased from the year of 2004. The impact of the entrance on enlarged market, the CEEC has reflected higher consumption of fresh milk and cheese, and production depends on the allocation of production quotas, and developments in the structure of production in the CEEC. With accession CEEC to EU, consumption of pork has risen. In the CEEC prices was (and are) generally higher, in particular for high quality pork, than in the EU-15. In contrast, poultry production is competitive in the CEEC and is expected to increase slightly to meet expanding demand.

Das and Uppal (2004), analyse systemic risk effects, arising from abnormal events, in a portfolio constituted by equity indices of 5 countries (four of which European indices). Their results show that systemic risk, perceived as a direct consequence of financial shocks, does affect the ability to diversify an investor’s portfolio. Hui (2005), emphasizes the fact that stock markets interdependence and co-movements are drivers of international diversification (portfolio diversification across countries). Facing an increase in those drivers, the ability to diversify across countries is reduced. Patev et al. (2006), with the intention of explaining Central and Eastern European equity markets co-movements, capturing market crisis impacts, also finds higher correlation and integration between these during crisis. Thus, benefits of portfolio diversification are diminished. Earlier, Meric and Meric (1997) develop a similar study for European equity markets, although with regards to the Black Monday of 1987, observing a significant decrease in international diversification due to increases in correlation between European and US equity markets after the crash.

Now we turn to the relationship between the German and Portuguese government bond markets. The aim is to test whether there was evidence of fight-to-quality from Portugal to Germany. According to the result we got from the DCC-IGARCH model, the correlation between 10-year German and Portuguese government bonds yields (Figure 8) is close to 1 from 2007 to Q2 2008, declining strongly thereafter due to the Subprime crisis. The same picture is obtained by analysing the levels of the yields, which were very similar in both countries until September 2008 (Figure 7). By the end of 2009, the correlation between the two markets was close to zero, becoming negative with the Greek sovereign debt crisis in early 2010, which ended up creating the need for external intervention on April 23 rd 2010. It is at the end of 2009 that the yields of both countries started to diverge, with the Portuguese yields reaching more than 16%, while the German ones decreasing to values close to 1%. Between November 2009 and April 2010, the correlation dramatically declined from 0.8 to -0.7. From that period on, the correlation oscillated between positive and negative values, being negative most of the time. Observing Figure 7, where we have the Portuguese and German yields, from 2010 to 2012, one can verify that the yields were moving in opposite directions to each other during most of this time, with German yields declining while the Portuguese ones were growing. This translates into the higher demand for low risk bonds due to the increase in risk aversion during the Euro sovereign debt crisis.

In order to check whether national peculiarities within the European Union can have an impact in the financial depth coefficient, the two variables chosen were the dummies PIIGS and Euro 6 . The first is used to see the difference when just analyzing the PIIGS countries, namely Portugal, Ireland, Italy, Greece and Spain. These five countries of southern Europe have similar economic environments and have a history of facing high unemployment, economic difficulties and political instability. Due to these difficulties, it is expected that the financial deepening has a higher impact in these countries, since they have to resort to finance in order to overcome them, leaving these countries with their characteristic high debt burden. Afterwards, by analyzing the role of the introduction of the Euro currency, it is expected that, by improving financial integration, it would result in a higher impact on financial depth and therefore in economic growth.

We strive to analyze the interaction between stock markets of United States of America (USA) and the major countries of the euro are, by implementing a dynamic conditional correlation model to capture return co-movements and a generalized vector autoregressive model to measure volatility spillovers where forecasted-variance decompositions are independent of sorting. Impacts of recent economic crises are considered, as we analyze data from January 2000 to January 2015. Countries involved are Belgium, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Portugal and Spain – 10 of the first 12 countries to be part of the euro area – and USA. Greece and USA appear as the two markets with lowest return co-movements with other countries, whilst France and the Netherlands show themselves as the strongest ones. As both the dotcom and the subprime crises intensify, the spillover ratio enlarges to reflect the increasing interdependency of financial markets during times of depression. Also, the sovereign debt crisis and the recent Russian financial downfall coincide with the growth of the spillovers ratio. In general, empirical results indicate high return co- movements and volatility spillovers across markets. Additionally, we assess the connection between systemic risk and volatility spillovers.

The data set makes the empirical study of slums possible in a large number of cities. Using Census data of more than 90 metropolitan areas we were able to estimate for the first time the supply curve of a developing country including physical constraints and informal house market with no man-made regulatory constraints. This geographic measure of unavailable land can be used in future work exploring topics as diverse as housing and mortgage markets, labor mobility, urban density, transportation, and urban environmental issues. The public properties are good predictors of informal housing markets and might be the main opportunity for dwellers to squat urban areas. The results show that slums increase supply elasticities, which makes hard to assess the impact of geographic constraints without considering the dual housing markets. The distribution of elasticities in Brazil has lower mean and variance than in US, but the rate of natural increase simulation shows a widespread dispersion of price growths for 2030.

Table 7 displays the VAR models of the three subsamples, each model consisting of the seven national equity markets. Looking at the first subsample, 2002-2007, there are not many significant coefficients besides the autoregressive lags, hence there are not many interdependences among European equity markets. The Belgian stock index positively influences Italian stocks, while Dutch equity negatively effects the stock market in Austria. These interdependencies are rather surprising since there is no obvious economic explanation for these findings. The VAR model of the crisis subsample, 2007-2011, leaves more room for interpretation. While the negative influence of the Netherlands towards Austria continues, the effect of Belgian stocks on Italian equity vanishes. Moreover, the Spanish equity market becomes the most influential market, positively affecting French, Italian and Dutch stocks. Pressure on Spanish equity leads to decreasing stock indices in France, Italy and the Netherlands, while positive developments in the Spanish market increase stock prices in these three specific countries. One might suspect this influence due to the negative development of the Spanish equity market. However, between 2007 and 2011, the Spanish equity index did not suffer the biggest losses. Table 15, found in the Appendix, shows that the equity index in Spain fell by only 45.0%, whereas the drops in Italy (59.0%), Belgium (51.6%) and Austria (67.8%) were larger. The reason for the dominant role of the Spanish equity market can be probably more attributed to its high volatility. Table 16 in the Appendix displays the annualized standard deviation of the financial markets. Behind Austria (38.83%) the Spanish equity market is the most volatile one (32.37%), illustrating the nervousness of the market, which subsequently seems to spillover to other equity markets.

the results achieved. Finally, the purely local volatility effects are larger for Austria, Ireland and Portugal (means of 81.75%, 81.91% and 88%, respectively) than for the other countries (the means range between 27% and 78%). To all purposes of our study all the Non-EMU countries and the Non-EU country behave like EMU-member countries, which give an idea of how integrated the euro countries are. Figures 4 to 7 show the time series evolution of the variance ratios for Germany, UK (representing the non-EMU countries), Portugal and Spain. We chose these countries because Germany and the UK are a wide representation of the European stock markets, and the most liquid ones; and Portugal and Spain because of the interest that those two indexes bring to our study once we are in their financial space. The European variance ratio generally increases over the sample period for all countries except (again) Sweden and the UK, for which it appears to be stable.

An additional channel for differential effects of alternative ways of fiscal consolidation arises when models take the credibility of fiscal consolidation into account. If governments succeed in convincing markets that specific consolidation measures will improve fiscal sustainability, interest rate risk premia should fall and agents’ discounted lifetime income rise, leading to higher aggregate demand. With high tax burdens, revenue based consolidations may lack credibility, as agents may correctly anticipate that additional tax increases will have to be reversed, e.g. due to their adverse impact on economic incentives. By contrast, expenditure reductions, in particular in politically sensitive areas such as household transfers, may convince agents that the consolidation effort is serious and will produce a lasting improvement in fiscal sustainability.

This paper follows this latter strand of literature and tests banking efficiency across EU countries in the wake of the recent crisis, using both Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) estimates and comparing the results obtained for a panel comprising the “old” EU-15 countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden and UK) and another panel comprising all of the current EU-27 members. The main conclusions point to the existence of statistically important technical inefficiencies that increased slightly after 2004 with the inclusion of the 12 new member-states. The obtained country efficiency rankings also allow us to conclude that countries that performed well in the EU-15 panel maintain their strong positions in the enlarged EU-27 panel. Furthermore, the analysis of the convergence process with the estimation of a beta-convergence model clearly shows that while there is convergence in banking efficiency across EU countries, it is a very slow process and not only the new member-states but also some of the “old” EU countries are still facing difficulties in adapting to the new market conditions.

1 table shows the dynamic of global competitiveness index presented by World’s Economic Forum. That is to say three Baltic states were not taken into account in 2000. The number of assessed countries was expanded from 58 in 2000 to 148 in 2014. The methodology of global competitiveness index was reviewed a few times during analysed period but the authors of the article make assessment in the framework of officially provided methodology. Comparing global competitiveness index 2000 and 2014 the significant change is determined. Only one country’s (Lithuanian) competitiveness has improved over 14th years. Some others’ competitiveness index have slightly deteriorated (Poland, Estonia). Two of transition countries’ competitiveness has fallen by 10 positions (Latvia, Check Republic). Other countries’ in transition competitiveness have fallen more than double behind more than 30 additional countries (Hungary, Slovak Republic). How Lithuania has remained its competitiveness over 14 years while other countries’ competitiveness deteriorated and some of them deteriorated a lot?

path is much more discounted through time, as compared, for instance, with the Baltic countries. In Latvia, a rather limited reversal of the financial sector liberal- ization is observed from mid 1996all the way to early 2003: resulting from the 1996 banking crisis, specific aggregate lending limits to regions (i.e., limits on exposure to non-OECD countries, bar the other Baltic republics) are imposed. In Lithuania, a limited reversal of the financial sector liberalization is observed from early 1998, also resulting from the experienced banking crisis: reserve require- ments on deposits on foreign accounts by non-resident are introduced; In Poland, no signs of any liberalization reversal are observed. Similarly to Hungary, the profile of its reform path is much more discounted through time; In Romania, no signs of any liberalization reversal are observed, but the reform path is a decidedly slow and cautious one: at the end of the sample, it has the highest (i.e., less liberalized) score for the “Full Index” of all countries in the sample: 1.60 (see Table V). In Slovakia, no signs of any liberalization reversal are observed. Here, the reform path is characterized by a broad stagnation since the Czechoslovak partition till 1998/1999, when, after a change in the political lead- ership, reforms are re-started, reaching after that levels similar to the other “Vise grad” countries in a rather quick fashion. In Slovenia, one of the most consis- tently cautious Member States concerning the advantages of integration and lib- eralization, reversals are indeed observed in all three indexes, since early 1995in the capital account and financial sector components, and from early 1997 in the stock market one. Since early 1999, with the entry in effect of the EU Association Agreement, across-the-board further (re)liberalization measures have been introduced.

An empirical analysis in the Australian, European and USA / Canada electricity markets reveals some evidence of an inverse relationship between the interconnection level and the joint volatility of prices. We used the correlation of prices between markets as an indicator of the interconnection level. This is in part a limitation in our empirical research, because other factors – not only the interconnection level – contribute to an increase in correlation. A possible way to overcome this indirect measure for physical interconnection could be the direct measure of the transmission lines and their electricity flows between markets. However, we had no access to this kind of information.

In the last few years, we have seen the importance of credit rating agencies (Standard & Poor’s, Moody’s, and Fitch) and their crucial task in providing information on which investors base their decisions. These agencies often had a more important role than the one played by governments. After the 2008-2009 financial and economic crisis, volatility in financial markets has increased markedly in several European Union (EU) countries, notably in the euro area, both in the sovereign debt market and in the equity market segment. While policymakers have looked at rating agencies as a possible source contributing to the increase in financial markets volatility, so far the literature does not seem to have tackled the link with the second moments of those financial variables. Indeed, such volatility may exacerbate the level of financial instability and its unpredictability, since high volatility levels are associated with higher risk perception of market participants. Moreover, such increased volatility and perceived risk can have similar unwarranted effects regarding macroeconomic uncertainty by amplifying output volatility.

According to this pattern, the value of the Spearman rank correlation coefficient is 0,586. This value indicates a monotonic relationship between the volume of foreign trade between Serbia and the mentioned countries, but it is not prominent. Additionally, a test of this hypothesis using a two-tailed test shows that the obtained result is not statistically significant. A similar result is obtained if we analyse the correlation coefficients between the data acquired by the BP filter, where the value of the Spearman coefficient was −0,086. It can be concluded that in this manner and with this number of countries involved, the causal relationship between the volume of foreign trade and business cycles synchronization in the case of Serbia cannot be proved. Further research may involve more countries and the analysis of some additional factors that may affect the relationship between these two values. At the same time, the small sample of the observed variables imposes a crucial limitation on the analysis conducted in this paper.

In the last few years, we have seen the importance of credit rating agencies (Standard & Poor’s, Moody’s, and Fitch) and their crucial task in providing information on which investors base their decisions. These agencies often had a more important role than the one played by governments. After the 2008-2009 financial and economic crisis, volatility in financial markets has increased markedly in several European Union (EU) countries, notably in the euro area, both in the sovereign debt market and in the equity market segment. While policymakers have looked at rating agencies as a possible source contributing to the increase in financial markets volatility, so far the literature does not seem to have tackled the link with the second moments of those financial variables. Indeed, such volatility may exacerbate the level of financial instability and its unpredictability, since high volatility levels are associated with higher risk perception of market participants. Moreover, such increased volatility and perceived risk can have similar unwarranted effects regarding macroeconomic uncertainty by amplifying output volatility.

ABSTRACT The study sought to analyze the indicators of public and private spending in Brazil and selected countries from 2000 to 2014. Public domain databases from different sources ob- tained through the Internet were accessed. The indicators related to public health expenditures decreased or did not increase and those related to private spending remained stable. Brazil was the country with the lowest share of public health spending, differently from what occurred in countries with similar, universal and public health systems. The data showed that spending on private health is relevant in the family budget. These findings point to a reduction of the role of the State as provider and financier of public health actions and services. As a result of the auster- ity measures, a decline in health spending was perceived, for example, in the percentage of Gross Domestic Product devoted to health, stabilized or slightly decreased in European countries. In Brazil, with the implementation of the ‘new fiscal regime’, public health expenditures are ex- pected to decline more, given the severity of the austerity policy.