Dr.DEBESH BHOWMIK

Dr.DEBESH BHOWMIK

Monday 8 July 2013

WORLD POVERTY IS STILL PERSISTING IN 2015









World poverty is still persisting in 2015
---Dr. Debesh Bhowmik

The World Bank has estimated the poverty line as the expenditure of 1.25 US$ per capita per day .On the basis of this measurement the world poverty is projected to decline at 970 million in 2015 compared to 1.2 billion in 2010 that is the poverty may reduce from 20.6% to 15.5% in which the progress of poverty in East Asia and the Pacific is promising because it will step down from 215 million in 2010 to 115 million in 2015 ie from 12.5% to 5.5%.The decline of poverty in South Asia is also more than expected since poverty stricken people was 507million in 2010 that will decreased to 406 million in 2015 – clearly a reduction from 31% to 23.2%.But the poverty amelioration in Europe and Central Asia and Latin America and Caribbean showed a little improvement .Even the Sub Saharan Africa will be able to cut poverty from 414 million to 408  million during the said period. The one and only exception is Middle East and North Africa where poverty rate has been rising from 2.4% in 2010 to 2.6% in 2015 ie from 8million poverty stricken people to 9 million. If ceteris paribus prevails, the target to achieve half of the world poverty stricken people has been failed. More over, the climate change and financial crisis may stipulate these figures.

2010(in million)
2015(in million)
World
1260
(20.6%)
970
(15.5)
East Asia and Pacific
215
(12.5%)
115
(5.5%)
Europe and Central Asia
3
(0.7%)
2
(0.4%)
Latin America and Caribbean
32
(5.5%)
30
(4.9%)
Middle East and North Africa
8
(2.4%)
9
(2.6%)
South Asia
507
(31%)
406
(23.2%)
Sub Saharan Africa
414
(48.5%)
408
(42.3%)
Source-WDR-2013,      
We also observed that world inequality is too high ie a wide gap between the income share of lowest and highest 20% and it is widening gradually. The income share of highest 20% in Argentina(49.4%), Belarus(35.8%),Brazil(58.6%), China(47.1%),Columbia(60.7%), Dominican(52.8%),Ecuador(53.89%),Indonesia(46.0%),Kyrgyz(41.4%),Mexico(52.8%),Moldova(41.2%),Nigeria(46.1%),Paraguay(56.4%),Poland(40.9%),Romania(36.1%),Thailand(46.7%),Turkey(46.0%) and Uruguay(50.9%).On the other hand income share of lowest 20% are in Argentina(4.4%), Belarus(9.4%),Brazil(2.9%),China(4.7%), Columbia(3.0%), Dominican(4.7%),Ecuador(4.3%), Indonesia(7.3%),Kyrgyz(7.7%),Mexico(4.9%),Moldova(7.8%),Nigeria(5.9%),Paraguay(3.3%),Poland(7.9%),Romania(8.8%),Thailand(6.8%),Turkey(5.5%) and Uruguay(4.9%) respectively during 2008-2010.
Naturally , poverty and inequality is the barrier of sustainable world development and in increasing human development in spite of several target oriented projects in fulfilling  MDG in the world economy as a whole.  

Wednesday 19 June 2013

39th G8 Summit








39th G8 Summit --- by Dr.Debesh Bhowmik

The 39th G8 summit was held on 17–18 June 2013 at the Lough Erne Resort, a five-star hotel and golf resort on the shore of Lough Erne in County Fermanagh, Northern Ireland. It was the sixth G8 summit to be held in the United Kingdom. The earlier G8 summits hosted by the United Kingdom were held at London (1977, 1984, 1991), Birmingham (1998) and Gleneagles (2005).
The official theme of the summit was tax evasion and transparency. However, the Syrian civil war dominated the discussions. A seven-point plan on Syria was agreed to after much debate. Other agreements included a way to automate the sharing of tax information, new rules for mining companies, and a pledge to end payments for kidnap victim releases. The United States and the European Union agreed to begin talks towards a broad trade agreement.
According to Cameron, it was also the most difficult issue addressed. However, the leaders were able to overcome major differences and agree to a path forward. A declaration signed by the eight nations outlines a seven point plan for Syria. It calls for more humanitarian aid, "[maximizing] diplomatic pressure" aiming for peace talks, backing a transitional government, "[learning] the lessons of Iraq" by maintaining Syria public institutions, ridding the country of terrorists, condemning the use of chemical weapons "by anyone", and instilling a new non-sectarian government. They called for UN investigations into the use of chemical weapons with the promise that whoever had used them would be punished. Although Syrian President Bashar al-Assad was not mentioned by name in the declaration, Cameron said it was "unthinkable" that he would remain in power.
Agreements were also reached on global tax evasion and data sharing. The G8 nations agreed to tight rules on corporate tax that sometimes allow companies to shift income from one nation to another to avoid taxes. They agreed that shell companies should have to disclose their true owners, and that it should be easy for any G8 nation to obtain this information. Going forward, corporate and individual tax information will be shared automatically to help detect tax fraud and evasion. The Organization for Economic Co-operation was tasked with gathering data on how multinationals evade taxes.
The G8 nations agreed that oil, gas, and mining companies should report payments from the government, and likewise that the government should report the resources they obtain. The measure was aimed at helping developing countries collect taxes from first-world companies operating in their territories. A declaration to stop paying ransom demands for kidnap victims was also signed.
During the summit the United States and the European Union (EU) announced they would enter into trade deal negotiations. Canadian PM Stephen Harper said the EU and Canada were close to wrapping up a similar deal after years of negotiations which should not be affected by the US-EU announcement.
Harper and Obama also had an informal meeting to discuss border relations during the summit. Harper said they discussed "a range of Canada-US issues that you would expect, obviously the Keystone pipeline."
The cost of the summit is expected to be about £60 million. The Northern Ireland Government will pay £6 million and the British Government will pay for the rest.

Saturday 15 June 2013

IMPACT OF STOCK MARKET VOLATILITY(PART-I)


Impact of Stock Market Volatility (Part-I)

-----Dr.Debesh Bhowmik

The conventional finance theory suggests that the stock market (excess) return, being a forward-looking variable that incorporates expectation about future cash flows and discount factors, contains useful information about investment and future output growth. Empirical literature provides substantial evidence in favour of this proposition .It is also seen from a number of recent studies that increased stock market volatility depresses economic activity and output . Empirical results presented by Campbell et al. (2001), in particular, are very important in this regard. They show that each of stock market volatility and excess return, when considered singly (i.e. when only one of these variables - either return or volatility - is considered) after controlling the lag dependent variable, is significant in explaining future output growth. But, when both volatility and excess return are considered as regressors (in addition to lag dependent values), volatility drives out return in predicting future output growth. As per the existing literature, stock market volatility may affects output growth through several possible channels, such as, (i) its link with market uncertainty and hence economic activity, (ii) association between market volatility and structural change (which consumes resources) in the economy, (iii) link of volatility with cost-of-capital to corporate sector through expected return. It is, however, not clear to justify why volatility drives out return in predicting output growth as observed by Campbell et al.(2001). Guo (2002) has discussed major arguments put forward by the proponents of volatility effects on output and has reconciled the evidence provided by Campbell et al. (2001) with earlier empirical evidence on predictive power of the stock market returns and finance theory. Based on a small model he argues that volatility may influence output growth (or may drives out returns in predicting output) in some specifications possibly because of its influence on cost of capital through its link with expected return.
But if cost of capital is the main channel through which volatility affects output then returns should play more important role in forecasting output growth than volatility does. He also provides empirical results to support this hypothesis. He derives relevant results for three different time periods; one longer than (but covering), one identical with, and another adding more recent years but shorter in length than the Campbell et al. (2001) sample period. Interestingly, using Campbell et al. (2001) sample, he finds that
the volatility drives out returns in predicting output growth because of the positive relation between excess returns and past volatility; if this relation is controlled for, excess returns show up significantly in the forecasting equation. In the liberalisation era, volatility in Indian financial markets is believed to have
increased/changed and thus there is a need to assess the impact of financial market volatility on output growth. With this background, this article presents some preliminary observations regarding link between stock market volatility/excess return and future output growth.
Some recent studies have shown that elevated stock market volatility depresses output. As per the conventional finance theory, however, it is the stock market (excess) returns that should have impact on future output growth. Currently, the issue is important in India, as there has been a perception that the volatility in Indian financial markets has increased/changed during the liberalisation era. Empirical results show that stock market volatility is strongly influenced by its own past values – pointing to the presence of significant volatility-feedback effects in the stock market. The volatility is also quite strongly related (at least contemporaneously) to excess return in recent years. However, roles of stock market return and volatility in predicting future output growth are not clear. Because, coefficients of lags of both these variables in the equation for future output growth are generally insignificant and in some cases have wrong signs, though during April 1997 to December 2002 only the volatility shows quite strong influence on output growth. Thus, there is a need to undertake further in-depth research for understanding the relationship between stock market return/volatility and future output growth in the context of Indian economy.

Thus, stock market uncertainty can have large effects despite the fact that households’ direct stock market participation is rather limited. Similarly, if stock market volatility can be viewed as an indication of how uncertain firms regard future developments, it can have a large effect on investment even if only a small fraction of firms in an economy
are subject to financing conditions determined by stock price movements. We provide empirical evidence on the relationship between stock market volatility and the business cycle and review the existing literature.
The empirical observation that stock market volatility tends to be higher during recessions points toward a negative relationship between stock market volatility and output. Fig-1 shows a scatter plot of U.S. quarterly percentage growth of real GDP against implied U.S. stock market volatility together with a fitted regression line.
The negative relationship between volatility and output growth is clearly visible. Scatter plots using historical volatility or GJR-based volatility instead of implied volatility show a similar negative relationship.
Although the empirical evidence presentedin the previous section indicates a close relationship between stock market volatility and economic fluctuations, the evidence is only suggestive.However, several papers document similar linkages using more detailed empirical approaches. The empirical study of Romer (1990) deals primarily with the onset of the Great Depression. However, Romer also presents estimates of the relationship between stock market volatility and consumption in the U.S.A.
Table-1: U.S. Ouarterly Stock Market Volatility
in Periods of Expansion and Recession

Fig-1:U.S. Stock Market Volatility and GDP Growth


for the post-war period. Using annual U.S. data ranging from 1949 to 1986, she concludes that a doubling of stock market volatility reduces durable consumer
goods output by about 6%, whereas the effect on nondurables is essentially 0. This ordering of the magnitudes of the effects is consistent with the idea that stock market volatility is closely related to uncertainty about future real economic activity. This is
because non reversibility gives rise to a lock-in effect that is particularly pronounced
during periods of high uncertainty.
Consider for instance a consumer deciding to buy a durable consumption good. Given the durable nature of the good and the uncertainty about future income, it may turn out that the good is either too modest or too luxurious with respect to future income. However, if the consumer waits until uncertainty is resolved, it may be easier to choose an appropriate good.Thus, by postponing the purchase of the good, the lock-in effect can be avoided and the benefit of doing so increases with the level of uncertainty. It follows that decisions that are irreversible to a larger extent are postponed, resulting in particularly pronounced reactions of durable consumption expenditures and investment expenditures to increasing stock market volatility.
Since investment decisions are presumably the least reversible, one would expect that stock market volatility has the largest effect on investment spending, followed by durable consumption and nondurable consumption. Note that if households substitute away from durable consumption goods into nondurable consumption goods because of higher uncertainty, then nondurable consumption may even rise during periods of high stock market volatility. Raunig and Scharler (2010) evaluate the uncertainty hypothesis by estimating the influence of stock market volatility on durable consumption growth, nondurable consumption growth and investment growth. Their analysis is based on quarterly time series data for the U.S.A. Based on a number of different estimates of time-varying stock market volatility, Raunig and Scharler (2010) find that stock market volatility exerts an economically and statistically significant effect on aggregate demand.
Moreover, they find that the adverse effect of stock market volatility on aggregate
demand depends on the extent to which decisions are reversible. Based on their richest specification (Table 2), they find that an increase in volatility by one standard deviation reduces the quarterly growth of durable consumption by around –0.70 percentage points, whereas the effect on the growth of nondurable consumption is only –0.14 percentage points. Investment growth responds with a lag of one quarter and declines by 1.12 percentage points.
Table-2:Effect of an Increase in Stock MarketVolatility by one Standard Deviation
on U.S. Consumption and Investment Growth


Hence, the decline in the growth of durable consumption and investment is larger during periods of increased volatility than the decline in the growth of nondurable consumption, which is again fully consistent with the predictions of the uncertainty hypothesis. In addition to being statistically significant, the estimated effects are also substantial in an economic sense. Stock market returns, in contrast to volatility, have a quantitatively smaller and often statistically insignificant influence on consumption and investment.
This result is consistent with Lettau and Ludvigson (2004), who also find that returns exert only a limited influence on consumption. The reason is that although permanent shocks to stock prices have a strong effect on consumption, most fluctuations in prices are transitory and exert only small effects on consumption.
Alexopoulos and Cohen (2009) identify uncertainty shocks using vector autoregressive methods. To measure uncertainty, they use stock market volatility measures, as in Raunig and Scharler (2010) and Choudhry (2003), and also an index based on the number of New York Times’ articles on economic uncertainty. They find that uncertainty shocks play an important role for the business cycle. In particular, uncertainty measured by the New York Times’ index accounts for up to 25% of the short-run variation in employment
and output. Choudhry (2003) analyzes the influence of stock market volatility on GDP and the components of GDP using an error-correction framework. Under the assumption that volatility follows a non -stationary stochastic process, he estimates the short-run and long-run dynamics of GDP components using an error-correction framework. His results confirm that stock market volatility has adverse effects on consumption and investment.
A different, but closely related, issue is analyzed in Jansen and Nahius (2003) They analyze how stock market fluctuations influence consumer sentiment in a sample of eleven countries. They find that in the vast majority of countries under consideration, consumer sentiment and stock returns are positively related. They also find that causality runs from stock returns to consumer sentiment rather than vice versa. Moreover, they conclude that the correlation between stock returns and consumer sentiment mirrors expectations about future economic conditions. Therefore, the evidence presented in their paper also provides some backing for the uncertainty hypothesis, in the sense that stock market fluctuations give rise to uncertainty about future economic conditions.
Note that although the uncertainty hypothesis suggests that causality runs from stock market volatility to the business cycle, this need not necessarily be the case. Although the early literature on the determinants of stock market volatility finds only weak linkages between stock market volatility and macroeconomic variables, recent empirical research (e.g. Engle et al., 2008; Diebold and Yilmaz, 2010) establishes important linkages between macroeconomic fundamentals and stock market volatility. In particular, Arnold and Vrugt (2008) find a strong link between macroeconomic uncertainty and stock market volatility using survey data from the Survey of Professional Forecasters maintained by the Federal Reserve Bank of Philadelphia. The authors find that rising uncertainty about future macroeconomic developments increases stock market volatility. Thus, taken together with the evidence presented above, it appears that causality between macroeconomic outcomes and stock market volatility is bidirectional.