搜档网
当前位置:搜档网 › On the Chinese B-share price discount puzzle Some new evidence

On the Chinese B-share price discount puzzle Some new evidence

On the Chinese B-share price discount puzzle Some new evidence
On the Chinese B-share price discount puzzle Some new evidence

On the Chinese B-share price discount puzzle:Some new evidence

Ali F.Darrat a ,?,Otis Gilley a ,Yanhui Wu b ,Maosen Zhong b

a College of Business,Louisiana Tech University,Ruston,LA,71272,USA

b

UQ Business School,The University of Queensland,Brisbane,QLD 4072,Australia

a b s t r a c t

a r t i c l e i n f o Article history:

Received 8February 2008Accepted 3October 2008JEL classi ?cation:G12G15

Keywords:

Dual-listed shares

Chinese stock markets B-share price discounts

Since February 2001,the Chinese Securities Regulatory Commission allowed domestic trade in foreign-currency denominated shares (B-shares)whose trade was originally restricted to foreign investors.We investigate possible effects of lifting the ownership restriction on the B-share discounts and explore why the discount persists even after removing the restriction.The discount is the percentage by which the B-shares are priced less than the otherwise identical Chinese-currency denominated shares held by domestic investors (A-shares).The results suggest that prices in the B-and A-share markets are closely linked over the long-run and that this equilibrium relationship strengthened in the post-lifting period.Our results further rule out information asymmetry as a reason for the continuation of the discount and support instead the importance of ?rm size and relative supply of the B-shares.

?2010Published by Elsevier Inc.

1.Introduction

Several emerging markets have dual-class stocks resulting from ownership restrictions imposed either by the government or the issuing ?rms.Capital control and sovereignty are often the reasons for imposing these restrictions (Domowitz et al.,1997;and Eun and Janakiramanan,1998).Recent literature discusses the pervasive im-pact of ownership restrictions on equity prices in various markets (Bailey and Jagtiani,1994).Evidence suggests that unrestricted shares commonly trade at premia relative to restricted shares due to several factors like information asymmetry,illiquidity,differential demand elasticity,short-sale constraints and differential risk aversion (Yang,2003;Chan et al.,2008,and Mei et al.(2008)).Two questions emerge:(1)what is the effect of lifting ownership restrictions on dual-class shares?(2)Do price differentials persist after the removal of these restrictions,and if so why?

The Chinese stock markets (segmented since the early 1990s)present an interesting case study.Historically,domestic investors were con ?ned to the A-share market while trading B-shares was available only to foreign investors in both the Shanghai Stock Exchange and Shenzhen Stock Exchange.Bailey et al.(1999)highlight an interesting anomaly.The B-shares are traded with substantial discounts relative to A-shares,though in other emerging markets with similar ownership restrictions (like the Thai market),the foreign (unrestricted)class shares are commonly traded at premia.

The ownership restrictions were partially lifted on February 19,2001,when the Chinese Securities Regulatory Commission (CSRC)allowed domestic investors to purchase foreign B-shares.Thus,do-mestic investors gained access to both local and foreign class shares,while foreigners were still prohibited from trading in local A-shares.When the markets reopened on February 28,2001,local investors began actively trading the B-shares causing a signi ?cant increase in share prices.Surprisingly,this failed to eliminate the B-share discount (discounts decreased on average from 80.7%to 48.1%).Using cross-sectional analysis,Chen et al.(2003)?nd liquidity and relative risk to be primarily responsible for the persistent B-share discounts while Mei et al.(2008)suggest the turnover rate of A-shares (in ?uenced by investors'overcon ?dence and speculative trading)explains 20%of the cross-sectional variation in the premia.

This paper revisits the B-share discounts and investigates possible reasons for their persistence even after lifting the restrictions using several techniques including cointegration tests and variance decom-positions.We also explore if the effects of factors responsible for the B-share discount have changed after removing the restrictions and examine possible reasons behind discount variations across ?rms in the post-lifting period.

2.Institutional background and data

In early 1990s,China established separate classes of stocks,one for Chinese investors (A-shares)and another for foreign investors (B-shares).Firms can issue both A-and B-shares in the two Chinese stock exchanges.Except for ownership restrictions,these shares have identical voting rights and dividend payouts.Foreign investors may trade only in B-shares transacted in US dollars in the Shanghai Stock

Journal of Business Research 63(2010)895–902

?Corresponding author.

E-mail address:darrat@https://www.sodocs.net/doc/244263776.html, (A.F.

Darrat).

0148-2963/$–see front matter ?2010Published by Elsevier Inc.doi:

10.1016/j.jbusres.2010.02.015

Contents lists available at ScienceDirect

Journal of Business Research

Exchange and in Hong Kong dollars on the Shenzhen Stock Exchange.Chinese investors trade only in A-shares denominated in Chinese currency (the RMB Yuan).These ownership restrictions were lifted on February 19,2001when the CSRC opened the B-share market to domestic investors.We begin the post-lifting period on June 1,2001when the CSRC banned investing in B-shares using foreign currency from February 19,2001until May 31,2001to guard against possible excessive volatility immediately after announcing lifting the restric-tions.By May 2003,there were 725?rms with A-shares and 54?rms with B-shares listed on the Shanghai Exchange,while the Shenzhen Exchange had 486?rms with A-shares and 57?rms with B-shares.Of these,84?rms issued both A-and B-shares.

Daily observations on closing prices and trading volume of the A-and B-shares from March 20,1998to May 22,2003come from Securities Industry Research Centre of Asia-Paci ?c (SIRCA)Database .Our data start one year after the 1997Asian ?nancial crises to minimize crisis-related distortions.We also use opening,high,low and closing daily prices of four stock market indexes from the SIRCA Databas e.Tsinghua Financial Database and MSCI world index of the DataStream provide information on the number of tradable A-and B-shares outstanding,total shares of each ?rm in the sample,and daily data on an A-share market index.

We exclude all ?rms in the Shanghai exchange without regular trading activities (e.g.,weak stocks listed under the Particular Transfer scheme)and also exclude four ?rms from the Shenzhen exchange (one under PT and three with missing data).Our sample contains 67?rms (35listed on Shanghai Stock Exchange and 32on Shenzhen Stock Exchange).

We divide our sample into four groups based on trading ex-changes:Shanghai A-shares (SHA),Shanghai B-shares (SHB),Shenzhen A-shares (SZA),and Shenzhen B-shares (SZB).We convert all prices to Chinese currency using of ?cial daily exchanges obtained from the Tsinghua Financial Database .To investigate the impact on the markets from lifting ownership restrictions,we divide our sample into two sub-periods (pre-and post-lifting).The pre-lifting period is March 20,1998to February 19,2001,while the post-lifting period starts June 1,2001(the date when restrictions on trading B-shares ended)and ends May 22,2003.

3.Empirical properties of the B-share price discount

The B-share price discount is the ratio of the price difference between the A-and B-shares to the A-share price,that is PA i ;t ?PB i :t

PA i ;t

.Despite removing the restrictions in 2001,Fig.1

shows that the B-share discounts persist across ?rms ranging from 28.1%to 71.4%and averaging 47.6%.A t -test shows that the overall mean of the B-share discounts is statistically signi ?cant in both periods.According to summary statistics of B-shares discounts (not shown here),the standard deviation of price discounts increased by

0.94%in the post-lifting period.To gauge the persistence of B-share price discounts,we compute the half-life statistic which estimates the number of days it would take for a shock in the series to diminish to half the original size.The average half-life is 12.8days in the pre-lifting period but increases to 16.8days in the post-lifting period.Thus,the B-share discounts became more persistent after lifting the restrictions.

B-share prices generally increased in both exchanges after lifting the restrictions.For example,the B-share market indexes of Shanghai and Shenzhen rose 171%and 253%,respectively,in the ?rst month after lifting the restrictions.The decreases in B-share price discounts over time were primarily driven by relatively larger increases in B-share prices.The average increase in B-share prices after removing the restrictions is 158.6%while A-share prices rose only 2.2%.Hence,price movements appear to have aligned prices in both markets.Does this imply that A-and B-shares have developed a long-run (cointegrating)relation?If so,has lifting the restrictions affected the price dynamics?We address these issues next.3.1.Cointegration analysis

We ?rst test for unit roots in A-and B-share prices using the Augmented Dickey –Fuller and the Phillips –Perron procedures.We select optimal lag lengths by the Akaike Information Criterion (AIC),allowing up to 20lags (20working days per month).We study the cointegrating relationship between A-and B-share markets using a vector error-correction model (VECM).The results provide useful information on long-term relations while allowing for short-run dynamics.

Let X be a 2×2vector of log A-share price (PA t )and log B-share price (PB t ).Then,

ΔX t =Γ1ΔX t ?1+…+Γk ?1ΔX t ?k +1+ΠX t ?k +εt ;e1T

where

Γi =?I ?A 1?…?A i eT;i =1…k ?1;“short ‐run ”matrix eTΠ=?I ?A 1?…?A k eT“long ‐run ”matrix eT:

Following Johansen and Juselius (1990,1992,JJ),we apply the maximum likelihood procedure to determine the rank of ∏and estimate αand β.Under the null hypothesis,there are r (0b r b n ,thus (n ?r )unit roots)cointegrating vectors,i.e.,∏=αβ′with αand βbeing n ×r (r [0,1])and we have:ΔX t =Γi ΔX t ?1+αβ′

X t ?k +εt

e2T

where Δis the ?rst difference operator,αis a (2×r )adjustment coef ?cient matrix,βis a (2×r )coef ?cient matrix of

cointegrating

Fig.1.The B-share discounts.Notes:the ?gure shows the average B-share discounts of 67?rms with A-and B-shares.The vertical line shows when the B-share market reopened for trading after lifting the ban.

896 A.F.Darrat et al./Journal of Business Research 63(2010)895–902

vectors,Γi is a (2×2)matrix capturing the short-run dynamic adjustments to changes in X t ,and ?t is a (2×2)white-noise error vector.We determine the lag pro ?le in the JJ test by the AIC procedure to avoid possible bias from arbitrary lag lengths selection (Gonzalo,1994),and use the trace test adjusted for small sample bias to determine the number of cointegrating vectors.

Results from unit root tests in both the pre-and post-lifting periods (not reported here)generally suggest that A-and B-share prices are integrated of order.The only exceptions are one stock in the pre-lifting period and nine other stocks in the post-lifting period that appeared stationary in levels.Consequently,we exclude these level-stationary prices from our cointegration tests.

We test for cointegration in the pre-and post-lifting periods to explore the nature of the long-run link between the A-and B-share markets.Table 1reports the JJ test results for the two periods.In the pre-lifting period,the results support signi ?cant cointegration (at least at the 10%level)in almost half of the sampled ?rms (31of 66).This evidence contrasts with Yang's (2003)report of no cointegrating relationship between A-and B-share markets based on market indexes from January 2,1995to December 29,2000.Our evidence also contradicts Fernald and Rogers (2002)who ?nd no cointegration between A-and B-share prices for 57sample ?rms over the period 1993to 1997.This disparity may be due to instability in the cointegration relationships.As we discuss later,results from Hansen and Johansen's (1993)cointegration constancy analysis suggest evidence of unstable cointegration vectors in the pre-lifting period.

Results for the post-lifting period in Table 1are unequivocal in their support of a stronger long-term equilibrium.Speci ?cally,these results suggest prices of more than 72%of all ?rms in the sample (42of 58)show signi ?cant long-run relations.Thus,A-and B-share prices appear to exhibit a stationary equilibrium relationship with the B-share discounts being more pronounced and stable in the long-term after lifting ownership restrictions.Note that about 28%of the ?rms in the sample (16out of 58)do not show common trends between A-and B-share prices in the post-lifting period.One possible reason for the lack of cointegration of these ?rms is that lifting the re-strictions failed to attract further domestic investment in B-shares of these ?rms.We also test cointegration over the full period by including a post-lifting dummy variable (0for pre-lifting and 1for post-lifting).Table 1further indicates that the cointegration relation becomes signi ?cantly stronger as all ?rms exhibit non-zero co-integrating vectors.This con ?rms that strength in the cointegration link derives mainly from the post-lifting period.

Hansen and Johansen outline a useful metric to assess the stability of cointegrating vectors.They construct a likelihood ratio (LR)statistic by comparing the likelihood value obtained from each recursive sub-sample with the likelihood value computed under the requirement that the cointegrating vectors are ?xed at particular constant values.Fig.2plots the LR statistics for the price-weighted portfolio of all 67?rms (the results are qualitatively similar for individual ?rms that became cointegrated after the event).Scaled by the 5%signi ?cance level of the χ2-distribution,computed statistics exceeding unity imply rejection of the null of cointegration stability.The results reveal that the cointegrating parameters are sample-dependent in the pre-lifting

Table 1

The Johansen and Juselius'cointegration test results.Notes:the trace statistics below are adjusted for small sample bias.The 90%critical values are 13.33for r =0,and 2.69for r ≤1respectively.N means no cointegration.Firms without N possess cointegration.Firm

The pre-lifting period The post-lifting period Full period with dummy r =0

r ≤1r r =0r ≤1r r =0r ≤1r

Panel A.Shanghai 113.630.50–––

36.30 6.44216.470.0618.77 1.8533.038.81310.89 3.65N

16.20 3.9231.9112.35413.940.0018.61 3.8127.229.64524.27 1.8517.02 3.9239.8914.50619.070.0517.31 4.0641.379.75710.610.10N 23.367.3437.5412.0589.950.49N 19.13 4.5126.267.43910.410.64N

–––26.907.751020.970.0315.480.5435.948.631118.75 1.0612.00 2.83N

34.5810.051222.400.9221.04 6.3443.0610.061311.040.67N 13.42 1.9742.9813.101425.760.1010.24 4.41N 41.738.251512.420.01N 8.630.82N 34.5811.681618.310.1023.38 6.6736.1411.1817 6.570.07N 13.210.46N 18.868.42188.590.11N 17.03 2.3821.369.271912.460.65N –––

37.609.292014.69 1.3918.24 2.0842.5810.15218.300.07N 20.81 4.0629.7711.112216.470.7114.71 4.9733.538.25238.430.22N

18.49 4.6042.8211.322418.320.31–––33.04 6.802514.490.2313.15 5.94N 43.1812.082613.040.72N

10.82 2.61N

37.969.2527––23.79 1.3536.4712.762816.90 6.0215.927.0733.9214.722910.100.47N –––

44.4611.923011.82 1.22N 14.11 5.0930.0410.253112.62 2.16N 15.96 6.8230.439.803212.29 4.64N 12.66 1.41N 22.649.34338.01 2.50N

8.99 2.72N

17.99 6.503423.74 1.9320.14 1.1435.51 6.4035

26.28

5.74

17.94

4.03

41.62

9.74

Panel B.Shenzhen 3630.23 2.5911.01 2.34N

52.498.353713.75 2.7324.54 2.5535.1010.233810.310.24N 15.63 2.1924.927.953911.72 3.40N

–––

37.6216.354018.11 1.8714.11 3.5438.817.004116.49 3.4116.90 4.5246.2812.4242 5.170.83N

18.40 4.5322.55 6.244314.90 1.1717.64 4.9727.39 5.484422.78 3.8611.21 1.02N

37.119.91459.20 1.18N 15.33 2.0629.579.25469.23 1.75N 20.42 4.9718.42 5.304710.630.53N 34.84 6.6833.377.53489.79 1.55N

14.02 1.2622.88 6.574918.62 1.2213.45 2.2642.319.245016.37 3.8419.23 5.8536.018.455111.76 2.26N 12.29 5.54N 32.568.915211.20 3.04N

16.58 5.7123.39 5.905322.340.4911.49 3.37N 31.817.955425.529.03 6.06 2.60N 38.9514.795510.23 1.31N 18.598.0126.78 5.875612.67 1.08N 7.46 1.88N 24.958.405712.96 1.83N –––

36.9811.955811.52 1.22N 28.52 4.7926.9610.875927.06 3.9415.367.2045.1916.806011.39 2.41N 18.11 2.4619.35 5.046115.20 4.10–––57.3712.84627.59 2.73N 13.700.2813.91 4.626312.520.81N 10.43 3.31N 35.7210.216420.447.0217.96 5.0228.4511.556510.700.73N

13.32 4.47N

32.3913.4166

18.73 2.63

20.480.55

19.55 3.74

(continued on next page)

Table 1(continued )Firm

The pre-lifting period The post-lifting period Full period with dummy r =0

r ≤1r

r =0

r ≤1r r =0

r ≤1r

67

8.170.61

N ––

–29.539.02

No.of ?rms with

cointegrating vectors 3142

67Price-weighted portfolio

8.82 1.13N

18.41 6.50

41.99

8.58

Panel B.Shenzhen 897

A.F.Darrat et al./Journal of Business Research 63(2010)895–902

period,but not in the post-lifting period.This implies that lifting the restrictions has promoted a much more stable linkage between the A-and B-share prices.

3.2.Forecast error variance decompositions

Chakravarty et al.(1998)and Su and Fleisher (1999)argue that information risk is signi ?cant in explaining the price gap between the dually listed shares.Chakravarty,Sarkar and Wu further suggest that the returns of B-shares appear to be led unilaterally by A-share returns.Nevertheless,results reported in other studies contradict this conclusion.For example,Chui and Kwok (1998)and Yang (2003)report that B-share investors are better informed,while Chen et al.(2001)fail to support information asymmetry.

We employ forecast error variance decompositions to capture the transmission of time-lagged information between A-and B-share markets and uncover the short-term dynamics of their causal linkages (Yang,2003).If the linkage between the two markets is stronger in the post-lifting period,then the proportion of return innovations of a given market explained by the other market's return innovations should increase.Under information asymmetry,the market with richer information should better explain the other market's innova-tions.Prior research typically uses Choleski decompositions to identify the proportion of the n -step-ahead forecast error variance due to shocks to variable i (A-share returns)and variable j (B-share returns).If the markets for the dual-listed shares are segmented,stock returns in a given market should not respond materially to innovations emanating from another market.However,if cross market linkage has actually strengthened in the post-lifting period,we should ?nd that return variations in either market explained by its own innovations have decreased while innovations stemming from the other market have increased in explanatory power.

Under cointegration,we calculate unexpected returns in the pre-and post-lifting periods as the forecast errors from a VECM model of returns:r t

+n =μ+∑n

l =1Θl r t

+l ?1

+αβ′

X t ?1+εt

e3T

where r t is the vector of continuously compounded returns of A-and B-shares at t [i.e.,r t =(r at ,r bt )′,where a =A-share,b =B-share];μis a vector of intercepts;Θl 's are autoregressive parameter matrices;and ?t is a white-noise residual vector.Under non-cointegration,we calculate the forecast errors from a VAR model.

Table 2displays our estimates from the Choleski decompositions for the pre-and post-lifting periods over alternative horizons (1,5,10and 15days).One practical issue is the sensitivity of the Choleski decomposition to the ordering of variables due to the existence of recursive contemporaneous causal structures (Swanson and Granger,1997).Following Hasbrouck (1995),we alternate the order of A-and

B-share returns to obtain two decompositions of the return co-variance matrix before taking averages.As panel A in Table 2indicates,the proportions of the innovations of A-share returns and B-share returns explained by their own innovations in both periods are large and very similar across the forecasting horizons.In panels B and C of Table 2,we report the average variance decompositions from the 15forecasting horizons for each stock in the Shanghai and Shenzhen exchanges,respectively.The results from the two exchanges are similar.Returns innovations of the A-and B-shares bi-directionally explain the return innovations of each other with almost the same magnitude.Therefore,consistent with Chen et al.(2001),but unlike Yang (2003),we ?nd no information asymmetry.Note that our analysis is different from Yang's in several respects.In particular,our variance decomposition analysis is bivariate in nature and cannot directly compare with Yang's results.Moreover,while Yang extends the method of Swanson and Granger (1997),our results are based on the averaging procedure of Hasbrouck (1995).

In the post-lifting period,the percentage of innovations of A-(B-)share returns explained by return innovations of the B-(A-)share signi ?cantly increases across all forecasting horizons.The magnitudes of the increase for both shares are also remarkably similar (from an average of 9%in the pre-lifting period to an average of 24%in the post-lifting period).This implies that the information linkage between the two markets is strengthened after lifting the restrictions.We also estimate the impulse response functions for each of the 67?rms using VECMs (under cointegration)and VARs (without cointegration).The results (available upon request)corroborate our ?ndings from variance decompositions indicating no information asymmetry between A-and B-share markets.Results from estimating the speed of response convergences between the A-and B-share returns to one unit shocks in each other also suggest that removing restrictions improved the informational ef ?ciency of the B-(but not the A-)share market.

Thus far we have focused on the cointegrating relationship between the A-and B-share markets and found compelling evidence that the B-share discounts are persistent over the long-term even after lifting the restrictions.While these tests highlight the underlying equilibrium relationships,they do not identify the potential sources of the persistent discounts.The next section discusses several possible explanations.

4.Possible explanations of the persistent B-share discounts 4.1.Proposed hypotheses

4.1.1.Differential risk levels

CAPM suggests that expected returns are determined by system-atic risk and market premium.Thus,differential risk levels between markets may contribute to the persistent B-share discounts.Bailey and Jagtiani (1994)support the differential risk level hypothesis

in

Fig.2.Hansen –Johansen's cointegration constancy test.

898 A.F.Darrat et al./Journal of Business Research 63(2010)895–902

the Thai market.Ma (1996)argues that investor attitude is correlated

with the cross-sectional price differential in the Chinese market.Domestic investors may have lower risk aversion and pursue short-term pro ?ts given the speculative natures of the Chinese markets.Chen et al.(2001)use return variance as a proxy for risk differentials and reject the differential risk hypothesis over the period 1992–1997.Unlike this paper,Chen,Lee and Rui's sample did not cover the post-lifting period.

We re-examine this hypothesis over an extended period that includes a market regime without ownership restrictions and use beta ratios of the two classes of shares (beta B/beta A)to proxy risk differentials.We derive the B-share beta from regressing returns of the Morgan Stanley Capital International (MSCI)World market index and the returns on China A-share market index orthogonalized on MSCI.Following Karolyi and Li (2003),we derive the A-share beta from regressing returns of A-shares on the returns of the A-share market index in the Chinese market.We expect a positive relationship between the beta ratio and the B-share discount since a higher risk level of B-shares (a higher beta ratio)leads to relatively higher required rates of return for B-shares.After removing the ownership restriction,one would expect further reductions in the B-share price discounts in stocks with higher beta since the domestic investor's required return is relatively lower.However,as an anonymous referee suggested,computing betas for two classes of shares using different market indexes may lead to inconsistency and biased computations.Thus,we check the sensitivity of our results by computing the beta ratios from the value-weighted market index.Our results assembled in Table 3are not particularly vulnerable to this issue.

4.1.2.Illiquidity discount

Amihud and Mendelson (1989)note,and Brennan and Subrahma-nyam (1996)con ?rm that investors require higher expected returns on relatively illiquid stocks to compensate for high trading costs.For the Thai market,Bailey and Jagtiani (1994)argue that liquidity is correlated with price differentials among dual-class stocks.Chen et al.(2001)provide supportive results for China and conclude that illi-quidity of the B-share market drives the price differentials.We ap-proximate liquidity by relative turnover [(trading volume of B/shares outstanding of B)/(trading volume of A/shares outstanding of A)].If removing restrictions increases liquidity of the B-share market,we expect a higher turnover ratio and a negative relationship with

Table 2

Hasbrouck's variance decomposition analysis.Notes:panel A reports results for the price-weighted portfolio of all 67?rms over several horizons for both the pre-and post-lifting periods.Panels B and C report the average results (over 15days)for each individual ?rm in the pre-and post-lifting periods in the Shanghai and Shenzhen markets,respectively.“A explained by A ”is the percentage of innovations in A-share returns explained by themselves,while “A explained by B ”is the percentage of the innovations of A-share returns explained by B-share returns.“B explained by B ”and “B explained by A ”have similar interpretations.Forecast horizon 151015Period

Pre (%)

Post (%)

Pre (%)

Post (%)Pre (%)Post (%)Pre (%)Post (%)Panel A:Average of VDCs across 67?rms A explained by A

92.1772.1591.5971.8789.9171.8689.1271.86A explained by B

7.8327.858.4128.1310.0928.1410.8828.14B explained by B

92.1772.1591.2572.2291.0371.9290.3671.92B explained by A 7.8327.858.7527.78

8.97

28.08

9.64

28.09

Firm

A explained by A A explained by

B B explained by B B explained by A Pre (%)

Post (%)

Pre (%)

Post (%)

Pre (%)

Post (%)

Pre (%)Post (%)Panel B.The Shanghai Market (average of 15forecast horizons)

189.3273.0210.6826.9888.7372.6211.2727.38293.1372.76 6.8727.2492.4771.727.5328.28394.9680.69 5.0419.3195.6379.38 4.3720.62492.4477.037.5622.9790.2977.419.7122.59593.0877.33 6.9222.6791.4679.538.5420.47690.1176.449.8923.5688.5272.9611.4827.04789.8284.0210.1815.9889.1984.2710.8115.73896.3680.57 3.6419.4396.6579.70 3.3520.30995.6977.42 4.3122.5894.7876.14 5.2223.861092.2576.887.7523.1291.4477.498.5622.511195.2075.58 4.8024.4295.1375.69 4.8724.311291.6075.118.4024.8991.2474.598.7625.411394.5183.95 5.4916.0591.4782.098.5317.911479.6977.0020.3123.0080.1576.0519.8523.951592.1687.807.8412.2093.1187.13 6.8912.871692.3066.467.7033.5493.1066.24 6.9033.761793.6384.32 6.3715.6892.3583.697.6516.311890.8176.989.1923.0390.5174.989.4925.021992.1478.617.8621.3992.2479.037.7620.972089.2771.2810.7328.7292.5670.507.4429.502187.5472.2212.4627.7886.4271.4313.5828.572288.8281.2911.1818.7187.0281.7712.9818.232390.6774.619.3325.3991.0173.458.9926.552491.7873.088.2226.9292.7372.657.2727.352589.5976.4110.4123.5987.9375.9812.0724.022689.3773.3310.6326.6789.4572.1410.5527.862790.0073.9310.0026.0789.8273.6610.1826.342894.1972.75 5.8127.2593.9672.73 6.0427.272984.3172.0615.6927.9483.7072.7316.3027.273088.1674.5611.8425.4485.7074.3214.3025.683193.8975.20 6.1124.8094.2673.86 5.7426.143282.0472.1017.9627.9081.8472.3118.1627.693391.3578.588.6521.4291.9578.088.0521.923495.2676.58 4.7423.4294.4974.77 5.5225.233593.3772.86 6.6327.1493.6272.62 6.38

27.38

Panel C.The Shenzhen Market (average of 15forecast horizons)3694.7181.34 5.2918.6694.6181.25 5.3918.753782.8170.1117.1929.8982.9468.4017.0631.603887.9385.1812.0714.8388.0584.5311.9515.473988.5772.5311.4327.4786.9372.6613.0727.344090.0770.899.9329.1189.6870.7410.3229.264186.0576.1813.9523.8289.9777.1210.0322.884289.5171.3810.4928.6290.6271.199.3828.814393.6171.33 6.3928.6794.1971.98 5.8128.024489.6784.9510.3315.0588.0385.0011.9715.004591.2374.518.7725.4988.6275.0611.3824.944683.3372.4516.6727.5582.0673.2317.9426.774791.9883.208.0216.8091.0782.81

8.9317.19

(continued on next page)

Table 2(continued )Firm

A explained

by A A explained by B B explained by B B explained by A Pre (%)

Post (%)

Pre (%)

Post (%)

Pre (%)

Post (%)

Pre (%)Post (%)4890.6984.069.3115.9490.1284.159.8815.854988.0578.3411.9521.6688.4776.0511.5323.955089.3273.5010.6826.5088.4773.3011.5326.705187.8173.4112.1926.5987.5772.7712.4327.235285.3074.1414.7025.8688.7873.6311.2226.375392.5977.577.4122.4391.3276.368.6823.645493.0580.72 6.9519.2893.3078.59 6.7021.415590.8178.769.1921.2493.4979.05 6.5120.955688.4673.0811.5426.9289.0771.4010.9328.605788.1276.4011.8823.6088.7475.8011.2624.205890.8574.909.1525.1090.1174.879.8925.135987.3476.5112.6623.4989.3176.5110.6923.496091.6081.828.4018.1891.2580.838.7519.176194.6176.25 5.3923.7593.1476.87 6.8623.136292.1573.717.8526.2994.5473.05 5.4626.956388.9477.8111.0622.1991.6176.898.3923.116492.5475.127.4624.8991.6674.228.3425.786592.0580.377.9519.6393.3383.10 6.6716.906683.2877.9116.7222.0982.5177.6217.4922.386789.1579.0910.8520.9188.8079.0611.2020.94Average 90.3476.589.6623.4290.2476.16

9.76

23.84

Panel C.The Shenzhen Market (average of 15forecast horizons)Table 2(continued )899

A.F.Darrat et al./Journal of Business Research 63(2010)895–902

the B-share discount.We also measure liquidity by the relative volume ratio but the results were qualitatively similar.We further examine if the liquidity condition impacts the adjustment of price differentials in the post-lifting period.

4.1.3.Corporate governance

From the perspective of international investors,signi?cant state ownership typically introduces bureaucratic and inef?cient manage-ment,leading to weak corporate governance.Thus,?rms with relatively high state ownership tend to generate lower returns.To explore the effect of corporate governance on the discount,we include the percentage of government shares to the total?rm shares as an explanatory variable.The political risk from inferior corporate governance is non-diversi?able for domestic investors but it is for foreign investors.Firms with better corporate governance(lower state ownership)should exhibit smaller B-share discounts since superior corporate governance is attractive to foreign investors willing to pay higher B-share prices.

4.1.4.Differential demand

Stulz and Wasserfallen(1995)offer the differential demand hypothesis stating that the demand elasticity for domestic securities differs across investors'nationalities because of their deadweight costs for holding risky assets.As Domowitz et al.(1997)argue, domestic?rms could restrict issuing shares to foreign investors and command higher prices so long as foreign investors have a relatively inelastic demand for domestic shares.Sun and Tong(2000)?nd a positive relationship between the B-share discount and the ratio of the outstanding number of B-and A-shares.Their results,like those of Chen et al.(2001),suggest that the associated demand curve is downward-sloping.More outstanding B-shares exert downward pressure on B-share prices thus increasing the B-share discount. Hence,the joint effect of an insuf?cient supply of A-shares and an oversupply of B-shares may exacerbate price differentia.We obtain some support for these contentions from computing monthly tradable and monthly returns of A-and B-shares for two years around the event day(The average tradable of A-and B-shares one year prior to the event were75,995,938and147,061,307,while these values one year after the event were89,429,014and161,717,937.The average monthly return of A-and B-shares one year prior to the event were 3.93%and6.56%,respectively,while the averages one year after the event were?2.81%and7.53%,respectively).

Following Chen et al.(2001),we use the ratio of outstanding B-shares to total outstanding A-and B-shares as a proxy of relative demand across?rms.If the differential demand hypothesis is valid, this ratio should be positively correlated with B-share discounts.We also expect stocks with limited B-share supply to exhibit higher price adjustments due to increased demand without the restriction.

4.1.

5.Size effect

Different?rm sizes may accompany risk differentials emanating, for example,from business risk,bankruptcy risk and information risk. These factors could impact expected returns.For example,larger?rms tend to be more information transparent and lower information risk may motivate investors to lower their required returns.Easley et al. (2002)argue that information risk positively impacts asset returns when individual investors possess private information.Bailey and Jagtiani(1994)report larger?rms are more attractive to foreign investors due to the availability of better information.

To detect the effect of?rm size on the B-share discounts,we use the logarithm of total market value to proxy?rm size.The total market value of a stock is the sum of the total tradable share value plus the total non-tradable share value.The non-tradable share value is calculated by the number of non-tradable shares multiplied by the average of the A-and B-share daily closing prices adjusted for the exchange rate.We expect a negative relationship between the B-share discount and?rm size since larger?rms have lower business risk, lower bankruptcy risk and better information availability.Conse-quently,foreign investors would be willing to pay higher prices for B-shares of larger?rms.

https://www.sodocs.net/doc/244263776.html,rmation asymmetry

Previous studies?nd mixed evidence on the information asym-metry in the Chinese market.For example,Yang(2003)reports that B-share investors are better informed,while Chen et al.(2001)?nd no evidence for information asymmetry.Our cointegration results rule out information asymmetry as a reason for the continuation of the B-share discount.To further verify our claim,our testing equations incorporate the?oating ratio(total tradable shares relative to total shares)to represent information asymmetry.The non-tradable shares include state,legal person and employee shares in which trading is strictly illegal.Firms with a higher proportion of non-tradable shares (lower?oating ratio)should have higher information asymmetry since the limited number of tradable shares would less likely attract investors and media coverage.

4.2.Summary statistics of the proposed hypotheses

Summary statistics(available upon request)of the B-share dis-counts and the proposed determinants for the average of67?rms over the pre-and post-lifting periods suggest that the average sys-tematic risk(beta)for B-shares is markedly larger than for A-shares. The average relative beta ratio is greater than1in both periods and

Table3

Explaining reductions of B-share discounts.Notes:panel A contains the results with betas estimated with different market indexes,while panel B reports the results with betas computed with value-weighted Chinese market index.Reduction1denotes the average difference of the B-share discount between the20trading days right before the lifting event and the20trading day after the market re-opening.Reduction2denotes the average difference of B-share discount between the100trading days right before the lifting event and the100trading day after the market re-opening.The dependent variable is reduction in the B-share discount of?rm i.See the text for de?nitions of the independent variables.An** indicates statistical signi?cance at the5%level while an*indicates signi?cance at the10%level.

Cross-sectional regressions

Constant Net pro?t Volatility ratio TTSN D/A rb i rt i f i MV i(SO B/SO A+B)i PST i R

–2 Panel A

Reduction10.626

(2.670**)0.017

(3.450**)

0.006

(2.430**)

0.015

0.920

?0.069

(?2.460**)

0.059

(2.840**)

?0.045

(?3.240**)

?0.021

?0.450

?0.043

(?2.130**)

?0.136

(?3.280**)

0.015

0.620

0.620

Reduction2 1.571

(5.5008*)0.016

(2.760**)

0.002

0.610

0.037

(1.840*)

?0.054

?1.590

0.017

0.670

?0.020

?1.170

?0.074

?1.320

?0.092

(?3.720**)

?0.276

(?5.430**)

0.041

1.440

0.549

Panel B

Reduction10.482

(2.070**)0.018

(3.850**)

0.002

0.790

0.025

1.710

?0.087

(?3.370**)

0.023

(3.580**)

?0.042

(?3.130**)

0.045

1.050

?0.045

(?2.380**)

?0.114

(?2.780**)

0.014

0.640

0.648

Reduction2 1.546

(5.240**)0.017

(2.840**)

0.001

0.250

0.040

(2.170**)

?0.060

(?1.840*)

0.005

0.610

?0.019

?1.130

?0.057

?1.040

?0.094

(?3.880**)

?0.272

(?5.230**)

0.042

1.470

0.548

900 A.F.Darrat et al./Journal of Business Research63(2010)895–902

increases from1.1to1.2in the post-lifting period.This increase is mainly due to the increase in the B-share beta(from1.015to1.250). The pair-wise correlations among the main variables,also available upon request,evince no signi?cant multcollinearity.Moreover,results from computing the variance in?ation factors rule out any multcolli-nearity issues in the regression analysis.

We measure the relative liquidity ratio by the turnover ratio between B-and A-shares.The average turnover of B-shares is only

0.37%(2.07%for A-shares)in the pre-lifting period,but rises to0.58%

(1.09%for A-shares)in the post-lifting period.While the B-shares market remains less liquid throughout the study period,B-shares were very illiquid before lifting the restriction.The average?oating ratio increased but remained below50%,implying a high potential for improving corporate governance.The average ratio of outstanding B-shares relative to total outstanding shares is0.69in the pre-lifting period and declined slightly to0.66in the post-lifting period.Finally, the average of total market value increased from2.9billion RMB in the pre-lifting period to4.4billion RMB in the post-lifting period. The large increase of total market value results largely from the gain in the B-share market value after lifting the restrictions.

4.3.Why do reductions in the discounts vary across?rms in the post-lifting period?

We next investigate possible causes for the varying reductions in B-share discounts across?rms after lifting ownership restrictions.We measure discount reductions by the difference between the average B-share discounts of20trading days before the event and20trading days after the re-opening day and alternatively,for100trading days before and after the event.Our selection of20and100trading days is arbitrary,but using shorter and longer periods yields similar results.

We regress reductions of the B-share discounts on the following independent variables:?rm's net pro?t(in logs),daily volatility ratio (B/A),the beta ratio(B/A),the?oating ratio of?rm i(f i),the total market value of?rm i in logs(MV i),the ratio of outstanding B-shares to total outstanding of both A-and B-shares,the top ten shareholding number in logs(TTSN),and the debt to asset ratio(D/A).Net pro?t, top ten shareholding number and the D/A ratio come from annual reports for December2000,while the beta ratio is derived from the unconditional beta of B-shares and A-shares for the pre-lifting period. Data on the remaining variables are averaged for the20trading days over the pre-lifting period.

Table3,panel A contains the results with beta ratios computed on the basis of different market indexes,while panel B uses betas com-puted from the value-weighted market index.For discount reductions immediately after market re-opening,panel A results generally suggest that most reductions occurred for?rms with the following characteristics:higher net pro?t,higher volatility in B-shares relative to A-shares,less B-shares outstanding relative to total shares out-standing,lower leverage,less active trading in B-shares during the previous20trading days,and relatively smaller?rms.When we examine the average reductions over100trading days after the event, we?nd that the size effect and the B-share supply ratio became even more pronounced,while several other factors lost much of their weight though maintained their correct signs.

Results in panel A further suggest that the speed and magnitude of price adjustments vary greatly among?rms with different character-istics.For example,B-shares with relatively higher risk(as re?ected in the volatility ratio)tend to be priced lower,providing hefty discounts. Removing the ownership restrictions made these stocks attractive for investors.However,the price adjustment seems short-lived since the impact disappears once we extend the window to100days.

For leverage D/A,within20days following the event,investors ?ooded the markets,targeting low leveraged?rms(more underlying value).Within the100-day window,those?rms with lower leverage had already had big reductions on price differences,and the impact of leverage had diminished.Relative turnover re?ects relative liquidity of B-shares.Chen et al.(2001)suggest that the price difference is smaller for stocks with relatively liquid B-shares.After the event,the magnitude of reductions in the price difference should get smaller for those stocks.However,once we lengthen the window,the impact loses signi?cance.This may re?ect the fact that the price gap was?lled rather quickly.

The size effect has a signi?cant negative coef?cient in both windows. This is consistent with our hypothesis that larger?rms have smaller price differences and thus smaller price adjustments after the event.The coef?cients for the relative B-share supply are signi?cantly negative in both estimations,suggesting that larger B-share discount reductions tend to occur to those stocks with relatively fewer B-share supplies.As a robustness check,we estimate other regressions using beta ratios computed with the value-weighted market index(see panel B). Generally,the results are not markedly different.A notable exception is that the volatility ratio becomes insigni?cant in both estimation windows,perhaps since the alternative beta ratios capture some of the risk factors embedded in the volatility ratio.Overall,the results suggest that the post-event demand for B-shares appears responsible for reducing the B-share discounts.Note that the average trading volume of B-shares over20trading days after the event soared by more than 1622%(compared to an increase of only25%for A-shares),while the B-shares of small?rms with limited supply have the biggest price adjustment.The proxy for information asymmetry fails to display any statistical signi?cance across different model speci?cations(consis-tent with our cointegration results).Note further that these cross-sectional results are broadly consistent with panel data regressions (available upon request)analyzing the effects of these variables in determining B-share discounts.

5.Conclusion

This paper revisits the debate on the B-share discounts in the Chinese stock markets.While the presence of signi?cant B-share discounts in the1990s under ownership restrictions is expected and well documented in the literature,the continuation of these discounts in the absence of restrictions since2001is puzzling and not fully explained.We discuss several possible explanations for the discount persistence and employ several empirical procedures to investigate the underlying determinants of the B-share discounts across?rms and over time in the pre-and post-restriction periods.We examine long-term relationships and short-term dynamics governing the B-and A-share markets.

Our results con?rm the presence of signi?cant B-share price discounts after removing the restrictions in2001.Unlike Fernald and Rogers(2002)and Yang(2003),we?nd that the A-and B-share prices are cointegrated in the pre-lifting period,and that cointegration sig-ni?cantly strengthened after removing ownership restrictions.These ?ndings support Darrat and Zhong(2005)and suggest that complete or partial removal of investment barriers enhances market integra-tion.Our results also reject information asymmetry as the root cause of the B-share discounts and further suggest that?rm size and relative supply of B-shares appear particularly important factors behind variations in the discount reduction across?rms since2001.Although foreign-currency restrictions were actually relaxed on June1,2001, domestic investors were still unable to acquire foreign B-shares because of limited access to foreign currency required to purchase B-shares. Moreover,returns from B-shares in Chinese currency suffer from double transaction costs(from the stock exchange and the currency exchange). Thus,capital controls may also partially explain B-share discounts.

Our results offer new insights for investors and corporate man-agers regarding B-share discounts.A lower B-share price discount implies further integration of the dual-class share market which would in?uence equity cost and further attract foreign investors pursuing diversi?cation.The?ndings in this paper could also be helpful for

901

A.F.Darrat et al./Journal of Business Research63(2010)895–902

policymakers in other emerging economies that have similar market structures and are contemplating the effects of market liberalization. Gradual reductions in the percentage of non-tradable shares should generally improve corporate governance and enhance?rms'perfor-mance over the long-term,all of which can minimize differentials in equity prices across markets.

Several lines of future research remain.More recently the Chinese government has also partially opened the A-share markets to quali?ed foreign investors.It would be interesting to examine the impact of these latest market changes on the price differentials between the A-and B-shares.Another interesting inquiry is to examine how A-shares of?rms having only A-shares and A-shares of ?rms having both classes(A and B)perform over the estimation period.Possibly,there was a systemic effect across the board that had an impact on the B-share price discount.

Acknowledgments

The authors thank,without implicating,the Editor and two anonymous referees for many helpful comments and suggestions. Thanks also to the participants in the Center for China Finance and Business Research Symposium for useful comments and to Tsinghua University for Database access.

References

Amihud Y,Mendelson H.The effects of beta,bid-ask spread,residual risk,and size on stock returns.J Fin1989;44:479–86.

Bailey W,Jagtiani J.Foreign ownership restrictions and stock prices in the Thai capital market.J Fin Econ1994;36:57–87.

Bailey W,Chung P,Kang J.Foreign ownership restrictions and equity price premiums: what drives the demand for cross-border investments?J Fin Quant Anal1999;34: 489–511.

Brennan MJ,Subrahmanyam A.Market microstructure and asset pricing:on the compensation for illiquidity in stock returns.J Fin Econ1996;41:441–64. Chakravarty S,Sarkar A,Wu https://www.sodocs.net/doc/244263776.html,rmation asymmetry,market segmentation and pricing of cross-listed shares.Theory and evidence from Chinese A and B shares;

1998.working paper Purdue University.Chan K,Menkveld AJ,Yang https://www.sodocs.net/doc/244263776.html,rmation asymmetry and asset prices:Evidence from the China foreign share discount.J Fin2008;63:159–96.

Chen G,Lee B,Rui O.Foreign ownership restriction and market segmentation in China's stock markets.J Fin Res2001;24:133–55.

Chen G,Lee B,Rui O,Wu W.Revisiting B-share discounts in the Chinese stock market;

2003.working paper University of Houston.

Chui ACW,Kwok CY.Cross-autocorrelation between A shares and B shares in the Chinese stock market.J Fin Res1998;21:333–53.

Darrat AF,Zhong M.Equity market linkage and multinational trade accords:the case of NAFTA.J Int Money Fin2005;24:793–817.

Domowitz I,Glen J,Madhavan A.Market segmentation and stock prices:evidence from an emerging market.J Fin1997;52:1059–85.

Easley D,Hvidkjaer S,O'Hara M.Is information risk a determinant of asset returns?J Fin 2002;7:2185–221.

Eun C,Janakiramanan S.International ownership structure,stock prices,and the?rm value.Glob Fin J1998;9:227–49.

Fernald J,Rogers JH.Puzzles in the Chinese stock market.Rev Econ Stat2002;84: 416–32.

Gonzalo J.Five alternative methods of estimating long-run equilibrium relationships.

J Econometrics1994;60:203–33.

Hansen H,Johansen S.Recursive estimation in cointegrated VAR models;1993.working paper University of Copenhagen.

Hasbrouck J.One security,many markets:determining the contributions to price discovery.J Fin1995;50:1175–99.

Johansen S,Juselius K.Maximum likelihood estimation and inference on cointegration with application to the demand for money.Ox Bull Econ Stat1990;52:169–209. Johansen S,Juselius K.Testing structural hypotheses in a multivariate cointegration analysis of PPP and the UIP for UK.J Econometrics1992;53:211–44.

Karolyi GA,Li L.A resolution of the Chinese discount puzzle;2003.working paper Ohio State University.

Ma X.Capital controls,and market segmentation and stock price:evidence from the Chinese stock market.Pac-Basin Fin J1996;53:1887–934.

Mei J,Scheinkman JA,Xiong W.Speculative trading and stock prices:an analysis of Chinese A–B share premia;2008.working paper Princeton University.

Stulz RM,Wasserfallen W.Foreign equity investment restrictions,capital?ight,and shareholder wealth maximization:theory and evidence.Rev Fin Stud1995;8: 1019–57.

Su D,Fleisher BM.Why does return volatility differ in Chinese stock markets?Pac-Basin Fin J1999;7:557–86.

Sun Q,Tong WHS.The effect of market segmentation on stock prices:the China syndrome.J Bank Fin2000;24:1875–902.

Swanson NR,Granger CWJ.Impulse response functions based on a causal approach to residual orthogonalizaiton in vector autoregressions.J Amer Stat Assoc1997;92: 357–67.

Yang J.Market segmentation and information asymmetry in Chinese stock markets:a VAR analysis.Fin Rev2003;38:591–609.

902 A.F.Darrat et al./Journal of Business Research63(2010)895–902

那一刻我感受到了幸福_初中作文

那一刻我感受到了幸福 本文是关于初中作文的那一刻我感受到了幸福,感谢您的阅读! 每个人民的心中都有一粒幸福的种子,当它拥有了雨水的滋润和阳光的沐浴,它就会绽放出最美丽的姿态。那一刻,我们都能够闻到幸福的芬芳,我们都能够感受到幸福的存在。 在寒假期间,我偶然在授索电视频道,发现(百家讲坛)栏目中大学教授正在解密幸福,顿然引起我的好奇心,我放下了手中的遥控器,静静地坐在电视前,注视着频道上的每一个字,甚至用笔急速记在了笔记本上。我还记得,那位大学教授讲到了一个故事:一位母亲被公司升职到外国工作,这位母亲虽然十分高兴,但却又十分无奈,因为她的儿子马上要面临中考了,她不能撇下儿子迎接中考的挑战,于是她决定拒绝这了份高薪的工作,当有人问她为什么放弃这么好的机会时,她却毫无遗憾地说,纵然我能给予儿子最贵的礼物,优异的生活环境,但我却无当给予他关键时刻的那份呵护与关爱,或许以后的一切会证明我的选择是正确的。听完这样一段故事,我心中有种说不出的感觉,刹那间,我仿拂感觉那身边正在包饺子的妈妈,屋里正在睡觉的爸爸,桌前正在看小说的妹妹给我带来了一种温馨,幸福感觉。正如教授所说的那种解密幸福。就要选择一个明确的目标,确定自已追求的是什么,或许那时我还不能完全诠释幸福。 当幸福悄悄向我走来时,我已慢慢明白,懂得珍惜了。 那一天的那一刻对我来说太重要了,原本以为出差在外的父母早已忘了我的生日,只有妹妹整日算着日子。我在耳边唠叨个不停,没想到当日我失落地回到家中时,以为心中并不在乎生日,可是眼前的一切,让我心中涌现的喜悦,脸上露出的微笑证明我是在乎的。

爸爸唱的英文生日快乐歌虽然不是很动听,但爸爸对我的那份爱我听得很清楚,妈妈为我做的长寿面,我细细的品尝,吃出了爱的味道。妹妹急忙让我许下三个愿望,嘴里不停的唠叨:我知道你的三个愿望是什么?我问:为什么呀!我们是一家人,心连心呀!她高兴的说。 那一刻我才真正解开幸福的密码,感受到了真正的幸福,以前我无法理解幸福,即使身边有够多的幸福也不懂得欣赏,不懂得珍惜,只想拥有更好更贵的,其实幸福比物质更珍贵。 那一刻的幸福就是爱的升华,许多时候能让我们感悟幸福不是名利,物质。而是在血管里涌动着的,漫过心底的爱。 也许每一个人生的那一刻,就是我们幸运的降临在一个温馨的家庭中,而不是降临在孤独的角落里。 家的感觉就是幸福的感觉,幸福一直都存在于我们的身边!

世界主要国家地区住房调控政策经验与启示

世界主要国家地区住房调控政策经验与启示 中国金融40人论坛特邀成员陈卫东 [ 2010-04-22 ] 共有0条点评 内容摘要:近年来我国住房市场蓬勃发展对改善居民居住条件、拉动经济增长和促进就业发挥了重要作用,但房价过快上涨、投机气氛渐浓,许多购房者被排除在市场之外,成为社会各界高度关注的热点问题。“他山之石,可以攻玉”,本文在归纳和总结主要国家和地区房地产市场调控背景、抑制泡沫政策和住房保障模式的基础上,提出了完善我国房地产市场调控、破解房地产市场难题的政策建议:政府要高度重视房地产问题,力争在“住有所居”和“保增长”之间取得最佳平衡,“保低放高”,继续扩大保障性住房建设和覆盖范围,增大住房市场交易和保有环节税负,实行以实物建房为主的住房保障模式,加快我国住房市场和住房保障的法制化进程。 关键词:房地产泡沫、住房保障模式、国际经验、住有所居 1998年以来,我国房地产市场蓬勃发展,对改善居民居住条件、拉动经济增长和创造就业发挥了重要作用。但最近几年,房价节节攀升,超出了许多购房者的承受能力,超出老百姓承受能力的房地产市场必定是不可持续的。“他山之石,可以攻玉”,归纳和总结世界主要国家和地区住房市场调控政策的背景、经验与教训,对完善我国住房政策、破解当前住房市场难题、促进房地产市场健康发展具有重要的借鉴意义。 一、主要国家和地区出台住房调控政策的不同背景 住房是人们生活的必需品,又是特殊商品。短期内需求大幅增加而供给难以及时跟进,决定了住房很容易成为投资品。生活必需品要求价格的稳定性和投资品价格的波动性之间的矛盾,是房地产市场最基本的矛盾。这个基本矛盾决定了不能把所有住房问题全都交由市场这只所谓“无形之手”去解决,客观上要求由政府“有形之手”加以调节,以弥补市场失灵。 (一)提供公共住房,保障居民“住有所居” 随着人口增长和经济发展,各个国家和地区住房矛盾不断突现,保障居民“住有所居”成为各个国家和地区住房调控政策的重中之重。新加坡有460万常住人口,国土面积仅699平方公里,人口密度大,土地资源十分有限。建国初期,面临严重的房荒,新加坡住房形势十分严峻。为解决住房短缺及其引发的社会问题,早在1960年新加坡政府宣布成立建屋发展局,1964年推出了“居者有其屋”的政府组屋计划,将政府工作的重点放在解决普通收入者的居住问题上。 香港政府干预房地产市场始于1954年,当时石硖尾大火导致5万多人丧失家园,政府不得不进行安置,并于当年成立了香港房屋委员会,负责建立和发展与商品房市场并行的公共经济房系统。1972年,房屋委员会制定了公共房发展规则,耗资54

关于我的幸福作文八篇汇总

关于我的幸福作文八篇汇总 幸福在每个人的心中都不一样。在饥饿者的心中,幸福就是一碗香喷喷的米饭;在果农的心中,幸福就是望着果实慢慢成熟;在旅行者的心中,幸福就是游遍世界上的好山好水。而在我的心中,幸福就是每天快快乐乐,无忧无虑;幸福就是朋友之间互相帮助,互相关心;幸福就是在我生病时,母亲彻夜细心的照顾我。 幸福在世间上的每个角落都可以发现,只是需要你用心去感受而已。 记得有一次,我早上出门走得太匆忙了,忘记带昨天晚上准备好的钢笔。老师说了:“今天有写字课,必须要用钢笔写字,不能用水笔。”我只好到学校向同学借了。当我来到学校向我同桌借时,他却说:“我已经借别人了,你向别人借吧!”我又向后面的同学借,可他们总是找各种借口说:“我只带了一枝。”问了三四个人,都没有借到,而且还碰了一鼻子灰。正当我急的像热锅上的蚂蚁团团转时,她递给了我一枝钢笔,微笑的对我说:“拿去用吧!”我顿时感到自己是多么幸福!在我最困难的时候,当别人都不愿意帮助我的时候,她向我伸出了援手。 幸福也是无时无刻都在身旁。 当我生病的时候,高烧持续不退时,是妈妈在旁边细心

的照顾我,喂我吃药,甚至一夜寸步不离的守在我的床边,直到我苏醒。当我看见妈妈的眼睛布满血丝时,我的眼眶在不知不觉地湿润了。这时我便明白我有一个最疼爱我的妈妈,我是幸福的! 幸福就是如此简单!不过,我们还是要珍惜眼前的幸福,还要给别人带来幸福,留心观察幸福。不要等幸福悄悄溜走了才发现,那就真的是后悔莫及了! 这就是我拥有的幸福,你呢? 悠扬的琴声从房间里飘出来,原来这是我在弹钢琴。优美的旋律加上我很强的音乐表现力让一旁姥爷听得如醉如痴。姥爷说我是幸福的,读了《建设幸福中国》我更加体会到了这一点。 儿时的姥爷很喜欢读书,但当时家里穷,据姥爷讲那时上学可不像现在。有点三天打鱼两天晒网,等地里农活忙了太姥爷就说:“别去念书了,干地里的活吧。”干活时都是牛马拉车,也没机器,效率特别低。还要给牲口拔草,喂草,拾柴火,看书都是抽空看。等农闲时才能背书包去学校,衣服更是老大穿了,打补丁老二再接着穿,只有盼到过年时才有能换上件粗布的新衣服。写字都是用石板,用一次擦一次,那时还没有电灯,爱学习的姥爷在昏暗的煤油灯下经常被灯火不是烧了眉毛就是燎了头发。没有电灯更没有电视,没有电视更没有见过钢琴,只知道钢琴是贵族家用的。

香港房地产金融市场的发展与特点(doc 9页)

香港房地产金融市场的发展与特点(doc 9页)

香港房地产金融市场发展特点与启示 2003-05-28 中国房地产金融作者:中国建设银行房地产金融业务香港培训班 2002年11月5日至12日,由中国建设银行总行房地产金融业务部孙冰峰副总经理带队,建设银行总行和部分分行房地产金融业务部的有关负责人和业务骨干以及总行人力资源部人员共 30人在香港进行了房地产金融业务培训。培训的主要目的是通过了解香港住房按揭市场情况及按揭业务运作,吸取香港房地产与房地产金融市场发展的经验教训,引进香港银行业的经营管理理念,学习和借鉴有益的业务运作方式、操作流程、产品品种以及有关制度体系,以不断规范中国建设银行房地产金融业务运作,加快产品创新步伐,提高市场营销能力,促进业务的持续稳定健康发展。 一、香港房地产金融市场的发展与特点 1.1 香港房地产市场现状 1.房地产价格持续大幅下跌,“负资产”借款人大量增加 自1998年亚洲金融风暴以后,香港房地产价格一路暴跌,截至目前已经平均下降了6成半左右,而且房地产市场仍未摆脱低迷和萧条,没有止跌回升的迹象。由于香港居民采取购房形式的置业与投资意识非常强,购房支出在香港居民的消费和投资支出中占有相当高的比例,因此,这次香港房价下跌持续时间之久、下跌幅度之大,给香港经济金融发展和社会稳定带来了很大的不利影响。 “负资产”一词的流行以及由此引发的一系列问题就是一个典型的例证。住房按揭是香港居民购买住房的主要手段,银行按揭贷款成数一般不超过房价的7成,但是由于房价的大幅暴跌,许多按揭借款人所购房屋的市价目前已远不及其按揭贷款的未偿还余额,成为“负资产”人士。根据香港金融管理局公布负资产住宅按揭贷款的最新调查(28家认可机构提供的资料):截至 2002年9月底,负资产住宅贷款总宗数70112笔;未偿还总额1180亿港元,占按揭贷款未偿总额的比例达22%;按揭成数已达128%(如以原按揭成数为七成计算,再假设近几年已还一成本金,则表明房价下跌了68%);平均利率大幅下调,为最优惠利率减0.76厘(以前高于最优惠利率)。“负资产”人士和负资产按揭贷款的大量存在,不仅影响了社会和经济稳定,也大大增加了银行按揭业务的风险。 针对上述形势,香港政府推出了包括停售公屋(指廉租住房,见后描述)抑制房价下跌等一系列措施,香港金融管理局也放宽了利率限制 (由原“最优惠利率十利差”变为“最优惠利率-2.5%”),并鼓励新按揭产品的创新。银行纷纷下调利率,推出加按、140%超按、MortgageOne账户(见后描述)等新产品防范风险,争取业务。发展商也以低于市价一至两成出售新楼,并提供二按(见后描述),送印刷费、律师费和提供低价装修、低价出售家居等新措施招揽业务。 2、满足不同收入阶层需要的住房供应体系

密室逃脱计划书

密室逃脱计划书 一、项目介绍 真人密室逃脱,打破了电脑游戏的局限和束缚,原汁原味的展现了密室的精髓,让玩家能过通过自己的双眼和双手,经过逻辑思考和观察力,不断的发现线索和提示,最重要的是团队的合作,能够顺利的逃脱。整个过程充满了未知性和不确定性,在紧张的场景氛围中,真正的融入到故事背景中去,这是电脑游戏所无法提供的乐趣。 真人密室也是在2011年才在国内正式起步,相较于国外已经成熟的体系,还未完全被大众所接受。2011年9月20日,第一家主营真人密室逃脱的俱乐部,在杭州正式成立。据可靠统计,全国目前已经有超过500家以上真人密室逃脱俱乐部,其中以北上广三地发展最为迅速。福州地区2013年3月左右,开始出现第一家真人密室逃脱俱乐部。我们的密室逃脱俱乐部名为八度空间,于2013年5月开始经营,属于福州地区比较早的密室商家。 二、市场分析 1.市场前景分析: 我们都是生活在平静生活中的普通人,每天重复着相同的事情,毫无生机。即便有着看电影、唱K、泡吧等种种休闲活动,但是对于追求新鲜的年轻人来说,闲暇时间还是显得越来越乏味。而要脱离这种提不起劲的困境,逐渐兴起的真人主题密室逃脱无疑会是一个最好的选择。密室逃脱实体游戏项目,既好玩刺激,又可以让每个体验者在游戏中充分调用智慧和体力,享受酐畅淋漓的畅快感觉。 据调查,福州2010年人口711万,现在福州的密室逃脱有6家(有实力),一年的订单数为22100个,票价35左右。和福州的土地面积差不多大小的洛阳和北京,与之比较,洛阳和北京的密室逃脱比福州早一年开始,2010年洛阳人口680万,现在洛阳一年的订单数为27200个,但是只有一家的密室逃脱(有实力),为寡头市场。2012年北京人口2069万,现在北京一年的订单数为49000个,票价70元,11家密室逃脱。福州与洛阳比较:店铺越多,接收客源面积越大,订单数越多。所以福州的未来市场的需求量为增幅状态。福州与北京比较:价钱越贵,订单数越少。所以福州的未来市场的需求量为增幅状态。 注:以上数据来源于美团网和中国知网,店铺收入不单单来源于网络的团购,还有其他收入,所以这只是代表部分的收入,所以当做消极悲观者的眼光来看待市场的需求量也是为增幅状态。 作为一个新兴行业,它的市场是还没有饱和的,你的质量比别家的好,有吸引力,客源量就会增加。结论:2014年起,至少一年,市场的需求量为增幅状态。 2.与传统娱乐项目对比的优势 ①体验刺激 或许过山车的尖叫只是生理上的一种释放,但是主题密室逃脱却能够从心理上让体验者感受刺激。各种精心布置的主题场景,暗含玄机的种种物品,还有与场景相配的音乐,这些都能够让体验者产生一种身临其境的感觉,从而可以更快地融入密室逃脱当中。当然,情节悬疑也是好玩的密室逃脱中一个重要影响因素。只有环环相扣的故事情节以及层层迭进的线索,才能够带动体验者更充分地享受推理和逃脱的过程。 ②高科技力挺 密室逃脱要做得好仅仅依靠故事情节和环境布置就太单薄了,高科技产品的使用也是使密室逃脱更加真实的一个诀窍。运用高科技物理机械和电子幻灯制造悬疑的场景气氛,炫酷的室内特技效果让场景显得更加逼真,而红外线、夜视仪等道具的使用也充分调动了体验者的紧张感和积极性。这些高科技的使用让密室逃脱不仅仅只是一个游戏项目,还成为一场科技产品展示的体验与经历。 ③价值无限 如果只将其当作是一个娱乐项目未免有点太低看真人密室逃脱了,因为在整个的逃脱过程当中,除了让体验者感受刺激和悬疑以外,还考验了每个体验者的智力、耐性以及良好的团队协作力。只有将团队中每个人找到的线索结合起来,才能够找到正确的出路。当然,这中间也需要有人指挥,有人配合,一旦团

香港住房政策与国内住房政策对比及启示

一、香港房地产市场的调控措施 透明的房地产市场交易信息。为遏制楼市投机行为、抑制房价过快上涨,香港政府不断加强新房屋预售、销售环节的透明度,降低开发商对房屋售价与现房供应的操纵,从而抑制了因新房销售信息不对称所引发的哄抬房价现象。香港政府对开发商预售、现售环节、信息披露、首次放盘量等方面出台了多项指引文件,还明确规定了有关预售新房(含楼花)示范单位的细则。 健全的土地管理制度。香港在坚持土地公有制的前提下,将土地使用权批租给受让人,土地批租主要采用公开拍卖、招标、私下协议和临时租约四种形式。香港有比较健全的土地法例体系,包括《香港房地产法》、《收回官地条例》、《土地征用法令》、《地契条款》、《拍卖地产条例》等。政府只是根据这些法例进行管理,实行有偿、有期、有条件使用土地。所有要使用土地的人都需要通过土地市场获得土地。既有垄断控制,又有自由转让。在楼市出现泡沫的时候政府采取增加住宅用地供应的做法,在楼市萧条时期政府采取减少土地供应的措施,以保持楼市的平稳发展。 完善的公屋制度。香港的公屋制度不仅包括政府出资建造建筑实体,还包括货币化的综援金制度。到1997年,香港650万居民中居住在出租公屋、政府补助出售房屋的人口达331.38万,占全港人口的51%。公租房制度与香港的房地产大规模开发几乎同步,不仅解决了众多中低收入者的住房问题,还为香港节约了土地资源,保持了社会稳定,提高了城市竞争力。

短期交易“额外印花税”。为了抑制投资者炒房,香港引入了短期交易“额外印花税”。目前,香港物业交易须缴纳最高4.25%的从价印花税,而“额外印花税”则分为三级税率:6个月或以内转售的交易,税率为该转售交易金额的15%;6个月以上至12个月之间转售,税率10%;12个月以上至24个月之内转售,税率为5%。换言之,持有物业的时间愈短,业主需要缴纳的“额外印花税”税率便愈高。 楼宇按揭成数调整。楼宇按揭成数也是香港调控楼市的主要手段之一,且效果比较明显。香港楼宇的按揭成数一般在5成左右。香港金融管理局根据楼市冷热程度适时调整楼市按揭成数。在楼市萧条时期上调楼市按揭成数,一般楼价越高按揭成数越高;楼市出现泡沫时下调楼市按揭成数,一般楼价越高按揭成数越低。2010年11月,香港金融管理局宣布下调楼宇按揭成数。新政一出,之前热火朝天的香港楼市顿入寒冬。据香港美联物业的统计显示,在楼市新政出台的首个周末,香港十大指标性二手楼盘的成交量已经比前一周减少近八成,二手楼看楼量普遍下跌五成以上,还有许多楼盘罕见地出现“零成交”。 二、香港与内地房地产政策调控的比较 香港楼市调控的针对性比内地强。一般来说,香港政府楼市调控的针对性很强,目标直指短期炒楼行为,加大炒家转手成本,进而遏制楼价快速上涨。在遏制纯投资购房者以金融杠杆炒楼的同时,也确保了真实自住型需求不受政策影响。所以香港楼市调控政策的短期效应比较明显,特别是楼市泡沫期间,每一轮楼市新政出台后的数周内,

小学生作文《感悟幸福》范文五篇汇总

小学生作文《感悟幸福》范文五篇 小草说,幸福就是大地增添一份绿意;阳光说,幸福就是撒向人间的温暖;甘露说,幸福就是滋润每一个生命。下面是为大家带来的有关幸福650字优秀范文,希望大家喜欢。 感悟幸福650字1 生活就像一部壮丽的交响曲,它是由一篇一篇的乐章组成的,有喜、有怒、有哀、有乐。每一个人都有自己丰富多彩的生活,我也有自己的生活。我原本以为,吃可口的牛排,打电脑游戏,和朋友开心玩乐就是幸福。可是,我错了,幸福并不仅仅如此。 记得有一次,我放学回到家里放下书包就拿起一包饼干来吃。吃着吃着,突然我觉得牙齿痛了起来,而且越来越痛,痛得我连饼干也咬不动了。我放下饼干,连忙去拿了一面镜子来看。原来这又是那一颗虫牙在“作怪”。“哎哟哟,哎哟哟,痛死我了……”我不停地说着。渐渐地,那牙疼得越来越厉害,疼得我坐立不安,直打滚。后来在妈妈的陪伴下去了医院,治好了那颗虫牙。跨出医院大门时,我觉得心情出奇的好,天空格外的蓝,路边的樟树特别的绿,看什么都顺眼,才猛然一悟,幸福是简单而平凡的,身体健康就是一种幸福! 这学期我发现我的英语退步了,我决定要把这门功课学好,于是,我每天回

家做完作业后,都抽出半小时时间复习英语,在课上也听得特别认真,一遇到不懂的题目主动请教老师。经过一段时间的努力,终于,在上次考试的时候,我考了97分。妈妈表扬了我,我心里美滋滋的。我明白了经过自己的努力享受到成功的喜悦,这也是一种幸福。 …… 每个人都无一例外的渴望幸福。不同的人有不同的感受,其实,幸福就是那种能在平凡中寻找欢乐、能在困境中找到自信的一种心境。同学们,幸福其实很简单,就在我们的身边,触手可及。用心去认真地品味吧,它一直未曾离开我们身边! 感悟幸福650字2 有的人认为幸福就是腰缠万贯,有的人认为幸福就是找到意中人,“采菊东篱下,悠然见南山”是陶渊明对邪恶幸福,“从明天起做一个幸福人,喂马、劈柴、周游世界。从明天起,关心蔬菜和粮食,我有一所房子,面朝大海,春暖花开。”这是海子的幸福。一千种人就有一千种对幸福的理解。 我对幸福的理解就是幸福使简单而平凡的,是无处不在的! 我的牙疼得奇怪而顽强不是这颗牙疼就是那颗牙疼;不是吃冷的疼就是吃热

香港地产模式不适合中国内地

香港地产模式不适合中国内地 社科院易宪容 那种高房价、高地价、高公屋率的住房发展模式不适合中国。绝大多数民众的住房问题,只能在政府某种政策帮助下进入房地产市场来解决。这就要求我们不仅要调整房地产市场产品结构,也得通过政策方式来调低房价。 在今年两会上,房地产问题成了代表们关注的热点。对此,不少代表提出了自己的看法,并希望用不同的方式来解决国内目前的高房价问题,解决中低收入民众的住房问题。在2006年政府工作报告中,对房地产问题也有更为详细的阐述。如,“继续把好土地、信贷两个闸门,坚持实行最严格的土地管理制度,坚持按照贷款条件和市场准入标准发放贷款。从严控制新开工项目。继续解决部分城市房地产投资规模过大和房价上涨过快的问题。要着力调整住房供应结构,严格控制高档房地产开发,重点发展普通商品房和经济适用房。建立健全廉租房制度和住房租赁制度。整顿规范房地产和建筑市场秩序”等。而把这些意见归结到一点,就是中国房地产市场采取何种发展模式以及中国的住房保障体系如何来建立的问题。 政府目前对内地房地产发展之思路,很容易让我联想到香港的住房发展模式,即高地价、高房价、高公屋居住率。在这种模式下,政府以高价将土地出卖给开发商,房地产开发商以高房价在市场交易。在这种高房价下,60平方米以下的住房占72%,90平方米以下的住房占90%,而近50%香港居民住政府供给的公屋。在这种制度安排下,尽管香港税收十分低,但是社会绝大多数财富通过房地产市场分别流向了政府(如政府庞大的土地基金)与房地产开发商(香港的最富有的人基本上都是通过房地产市场起家的),造成了严重的社会财富两极分化。

同时,由于房价过高、公屋率过高,整个香港居民的住房福利水平严重下降。这不仅表现的香港居民的住房面积过小,而且表现在香港绝大多数居民所住房子的周边环境恶劣。可以说,香港这种住房发展模式是香港特定条件下的产物。 政府目前对内地房地产发展之思路,处处似乎都表现出要仿照香港房地产的发展模式。比如,无论是去年中央政府关于宏观调控的文件,还是“十一五规划”关于房地产的发展概要,都是以稳定房价为目的,且都显示出中国的房地产市场发展正在走向香港模式。政府有这种思路,房地产开发商更是尽情地发挥了。比如,以高房价来带动高地价;再比如,中低收入者的住房问题基本通过政府资助来解决(建立中国的住房保障体系,加大政府对经济适用房与廉租屋投入……)。然而,这种模式究竟适合中国吗?这种模式对谁最有利?最大的受害者又是谁? 作为一个处于转轨过程中的发展中国家,中国绝大多数民众目前仍处于中低收入水平的状态下,如果绝大多数民众的住房都要通过国家的住房保障体系来解决,政府的财政有这种承受能力吗?如果没有,中国住房保障体系的资金又从何而来?在目前的情况下,国家财政显然是没有这种能力建立香港那种庞大的公屋体系的。而且,即便是政府有能力来承担,那么又将通过何种方式来分配呢?如果这种分配体系不能够市场化,那么不就又退回到1998年货币化住房改革之前的老路上去了吗? 一些人之所以要把中低收入民众住房问题归结到政府责任上去,一方面是因为房地产开发商要把中国绝大多数民众赶出房地产市场,另一方面也是在为推高房价提供借口。当然,这和政府目前采取的这种模仿香港的住房发展模式也不无关系。

中国大陆地区与香港地区汉语外来词对比研究

内容提要 外来词是一种普遍的语言现象,本文在对汉语外来词的由来及其历史状况作出初步探讨的基础上,着重比较中国大陆地区与中国香港地区在外来词借入过程中所存在的差异,并进一步探索分析造成这种差异的社会历史文化等诸多方面的因素。

目录 0.引言 (1) 1. 汉语外来词研究 (2) 1.1汉语外来词的发展历史 (2) 1.1.1第一次高峰.古代西域/佛教 (2) 1.1.2 第二次高峰.近现代西学东渐 (3) 1.1.3 第三次高峰.当代改革开放 (4) 1.2 外来词引入的六种方式 (5) 1.2.1音译 (5) 1.2.2意译 (5) 1.2.3形译 (5) 1.2.4半音半意译 (6) 1.2.5音译加表意字 (6) 1.2.6直用原文 (6) 2. 香港地区汉语外来词与大陆地区汉语外来词的差别8 2. 1译法的不同 (8) 2.1.1普通话曾用过音译,但后改为意译而香港则一直为音译8 2.1.2普通话为意译,而香港则为音译 (9) 2.1.3香港为音译,普通话原来就有 (10)

2.1.4同是音译,但用字却不同 (10) 2.1.5同是意译,译法不同 (11) 2.2 语义的变异不同 (12) 2.2.1 词义的变异 (12) 2.2.2 词用的变异 (13) 2.2.3利用词义的变异造变义混合词 (13) 2.3差别的原因 (14) 2.3.1不同的历史文化积累、社会环境,从根本上造成了 两地对外来词的不同态度和倾向 (15) 2.3.2 两地不同的语言使用环境 (16) 2.3.3 香港地区独特的外来语借入过程 (17) 2.3.4 粤语独特的语音特色 (18) 3. 结语 (20) 注释 (23) 参考文献 (24) 论文摘要(中文) (1) 论文摘要(英文) (1)

小游戏----密室逃脱

活动名称:大班数学探索活动----密室逃脱 设计思路: 偶然的机会听孩子们分享自己玩游戏的经验,发现他们对比较有挑战性的游戏如密室逃脱闯关等非常感兴趣,于是,我就想:能不能用游戏这样一个载体,将数学这一学科的某些知识呈现在里面?于是,我就按照自己的理解,把生活中常见的物品分成几个层次:将游戏材料有的散点状放置,有的向不同方向有序排列,有的重叠排列等,投放到科学探索区内,观察幼儿的游戏情况。在幼儿操作材料过程中,我发现他们数数时的方法、速度、能力等都有异同,因此,我梳理了幼儿的一些数数经验,结合大班幼儿的年龄特点,生成了本次活动。 活动目标:1、在幼儿观察、比较、推理中,尝试通过操作材料,探索可以将物品数正确的方法。 2、仔细倾听同伴的想法,乐意分享观察方式。 活动准备:幼儿操作卡(每人2张)、PPT4张、笔、夹子、照片。 活动过程: 1、呈现密室,激发幼儿兴趣:了解幼儿数数的能力。 出示PPT1,谈话引出课题 1、讲解密室逃脱游戏规则。 师:今天,老师带你们玩密室逃脱,你知道这个游戏怎么玩吗?师讲解游戏规则:密室逃脱就是我们进入房间,通过数房间里各种物品的数量来推算出房门的密码,从而打开房门,逃出密室。 2、报数游戏:让幼儿数数接龙。 师:清点人数完毕,请你们摆一个最漂亮、最帅气的姿势跟老师们打个招呼,不然,待会出不来可能没有人来救你。 3、谈话:你能数到几? 师:刚才集体报数完全正确,现在,我问问小朋友,你最多能数到几?我说一个数字,你接着往下数,往下数()个数。(教师一方面关注幼儿数数是否正确,另一方面关注幼儿从十位数数到百位数数的能力,同时,观察其他幼儿,聆听每个幼儿的数数情况。)师:小朋友们都能数到很大的数,真了不起!但你们数数的正确性怎么样呢?老师会在游戏中检查你们的本领。 2、进入密室:探索正确数数的方法。 第一环节:来到密室一:出示PPT2 师:我们已经进入密室,现在,赶紧来找找怎打开房门的密码。(引导幼儿找到门上的密码锁,通过寻找密码打开锁从而逃出密室。)密码锁提示我们找哪些物品? 1、幼儿完成相应操作卡,正确数出PPT上相框、靠枕、猫及红花的数量。 师:密码锁提示我们:要仔细找找密室里有几幅相框?靠枕有几个?猫有几只?红花有几朵?把你观察到的结果记录在对应的空格里,不会写数字的用圆点代替。(教师重点关注猫和红花的记录情况) 2、幼儿交流自己的观察结果。教师及时提升幼儿表达的数数要领: A、一起告诉我,相框有几幅?靠枕有几个?师总结:东西比较少,数起来很方便; B、数猫可就不简单了,请您告诉我,你数到有几只猫?你在哪里找到了第×只猫?师总结:要把东西数清楚是需要讲究方法,要从上到下、从左到右、从前到后,只要按照一定的顺序就能数清楚。(教师要重点关注幼儿的表达,如方位是否正确,语句是否完整,还要关注幼儿数猫的方法) C、这里的花特别多,你是怎么数的?你是怎么数的?黄花能不能数进去?引导幼儿说出2个2个一起数的规律。师总结:数东西的时候,不但要讲究顺序,而且要仔细看清楚题目,

香港的公屋

香港的公屋 周昀皓发表于2013-04-16 08:57 一般人想到香港可能会联想到大厦林立的商业区,或者亮丽的购物中心,但其实对很多香港当地人来讲,公共屋村(简称公屋)才象征了香港普罗大众的生活。 从香港的统计来看,香港人口约有710万人以上,而且这数字年年有上升的趋势,香港土地面积是1104平方公里,大约是上海的1/6,人口密度自然非常高,在世界上也是头三位高密度地区之一,而且香港的地形是山地较多,平地较少。 所以,一般住宅的购入金额非常高,只有非常少的一部分富裕阶层才有能力拥有。一般市区高层住房(私家楼)的价格,大约需要一个普通香港人11年的薪资,比起在日本东京首都圈买房需要的5-7倍年薪,在香港买房更为困难。 居者有其屋 为了解决香港地少人多、楼价高带来的中低收入人士住房问题,香港政府通过公屋政策及政府资助,给大部分香港人提供了一个安身之所。 目前,香港700多万人口中约半数都住在这类政府资助的公营房屋里,其中租住公屋的人数为三成。以公屋为例,每月租金只为一般低收入家庭收入的一成左右。每个屋村都有配套的文娱康乐设施,球场、公园、诊所、商场和商店街等。 以一般一家四口为例,居住面积大约只有50平方米,生活空间较为狭窄。但香港的公屋制度不但保障了每个香港人都能获得城市生活的基本居住需求,更让每个人都有一个安定的起点。 很多香港人都在公屋长大,毕业后或许先帮父母搬去环境更好的公营房屋(例如居屋),然后自己再存钱搬去私家楼。或结婚后,夫妇继续住在旧的公屋单位里,买复数的住宅单位作出租或炒卖的投资目的,最终达到更好的生活水平。 在街头访问一般的香港单身人士,人生最大的目标是什么? 听到最多的回答是“买屋”。比起结婚优先考虑买屋,这可能是像香港这类环境才有的现象。狭窄的居住环境或许正是鼓励香港人一步一步往上获得更舒适的生活环境的动力,也是很多人的共同原点,或许正因为如此,很多香港人都对公屋带有很特别的感情。

关于以幸福为话题的作文800字记叙文5篇

关于以幸福为话题的作文800字记叙文5篇 ----WORD文档,下载后可编辑修改---- 下面是作者为各位家长学生收集整理的作文(日记、观后感等)范本,欢迎借鉴参考阅读,您的努力学习和创新是为了更美好的未来,欢迎下载! 以幸福为话题的作文800字记叙文1: 那是我生病后的第三天,妈妈从早上五点就起来为我准备早点。她蹑手蹑脚地走着“针步”,下楼煮早点,“啪”的一声,妈妈打开了煤气。在拿肉丝,打鸡蛋的她全然不知我正躲在楼梯口“监视”着她的一举一动。不一会儿,蛋炒好了。 她开始切肉丝,一不小心,妈妈的手指切破皮了,鲜血正一滴一滴地流下来,为了不影响我的睡眠,她把手指放在嘴里吸了一下,坚持把剩下的肉丝切完。 此时的我,心中犹如打翻了五味瓶,眼里的泪像断了线的珍珠般掉了下来,我再也忍不住了,一个劲地冲到妈妈面前,她赶紧把手背了过去,生怕让我知道了什么。 她吃惊地问我:“妈妈太吵了,吵到你了?”“不,不,没有”她见我这么早起来就让我再回去补个觉。我关心地问:“妈,你的手没事吧?”她吱唔着说:“没事,擦破点皮,不碍事!”我仔细地帮她清洗了伤口,贴了一片创可贴。 吃饭时,妈妈一直地往我碗里夹肉,“孩子,病刚好,多吃点!”可是我见她始终都没吃一块肉。我也夹了两块放在她的碗里。“儿子懂事了,你自己快点吃吧!补身体要紧!”我冲她点点头笑了笑,“嗯。” 这就是幸福,一份简简单单的幸福!我祈祷这幸福能伴我成长。 以幸福为话题的作文800字记叙文2: 在我眼中,成长就是记录我们长大过程中一点一滴的小事情的,而幸福就在这点点滴滴中。 在我的成长记忆中,永不磨灭的是2017年11月的一天。妈妈要去云南,妈妈早上四点半要到指定地点集合,这么早,妈妈要两三点就起来,可是最近我咳嗽比较严重,所以天天给我煮萝卜汤喝。 “叮铃铃,叮铃铃”闹钟叫了起来,把我从睡梦中吵醒,一醒来,去找妈妈,

香港公租房

二、公租房管理模式的国际经验比较 (一)经验介绍 香港特别行政区,面积1104 平方公里,分为18个行政区域,约706万人口,香港地少人多,寸土寸金。1953 年12 月, 香港九龙石硖尾寮屋区遭遇火灾, 五万多居民变得无家可归。香港政府为安置因为火灾而失去住房的居民采取了急救计划,为灾害的受害者和赤贫人员兴建了一些紧急及基本的安居住所, 也是从那时起, 香港政府把公共住房变成了政府建设的计划。自1954 年开始实施公屋制度起,经过50 多年的努力,香港政府通过住房保障制度较好地解决了香港低收入群体的住房问题,成为世界上解决住房保障问题的一个成功典范。 香港政府于1973年4月1日颁布并实施了《香港房屋条例》,从并成立了专门的法定机构—香港房屋委员会(以下简称“房委会”)。房委会主席由运输及房屋局局长兼任,房屋署署长则为房委会副主席。房屋署是房委会的执行机关。除主席及副主席外,房委会成员还包括两名官方及26名非官方委员,全部由行政长官委任。所有非官方委员都是以个人身份接受委任。 根据房屋委员会的资料,至2011年6月,香港共有公屋72.13万套,超过200万香港人居住其中,约占香港人口的1/3。香港的住房市场包括四个部分:公营永久房屋,47.7%的香港人居住在公营永久房屋中,其中租住单位30.0%、资助出售单位17.7%;私人永久房屋51.8%;公营临时房屋(自2006年起不再适用);私人临时房屋0.5%①

(数据截止2011年第三季度,下同)。从住宅套数上看,公营房屋共计1137千套,其中房委会公营租住房屋单位708千套,房委会中转房屋单位5千套,房协租住单位34千套,房委会资助出售单位374千套,房协会资助出售单位16千套;私人房屋1433千套。类比我国公租房在建设档次、供给方式和保障对象上的情况,香港的公营租住房屋具有较高的借鉴意义。 全港公屋主要分布在四个区域内,分别为市区(包括港岛及九龙),扩展市区(包括东涌、沙田、马鞍山、将军澳、荃湾、葵涌及青衣),新界(包括天水围、大埔、粉岭、上水、屯门及元朗)和离岛(不包括东涌)。房委会设有公屋轮候册,以便为符合资格的申请人提供公租房,轮候册可于各屋办事处、分区租约事务管理处、深水房屋事务询问处、房屋署公屋申请分组及各区民政事务处免费索取。申请人根据自己的实际情况填写公屋轮候册,房屋署对所有符合资格的公屋申请者依先后顺序进行登记,并将严格依照轮候册上的申请书编号及申请人所选择的地区,依次办理审查及配房手续。所有申请者必须通过公屋轮候才能获得公屋配置。 1.公租房保障对象的界定标准 (1)配租对象 房委会根据申请人不同,将公租房计划分成四种类型。(1)一般家庭申请计划。这种申请计划主要是以家庭为单位,向房委会提交申请。申请人在填写公屋轮候册时,必须满足下列基本条件:申请者必须是年满18周岁,其家庭成员拥有在港永久居住权;18周岁以下的

最新整理高中关于幸福的议论文800字范文3篇

最新整理高中关于幸福的议论文800字范文3篇 范文一 什么是幸福?当我把一个棒棒糖递给六岁的邻居小妹妹时,她满足的笑容告诉我,这是她的幸福。当我轻轻地走过妹妹的写字台时,我瞥见埋在桌上的妹妹的僵硬的表情。我笑笑,走近,她抬头,水汪汪的眼睛望着我,似乎带着某种渴求。我说:出去玩吧!她笑了,蹦蹦跳跳地跑了出去。我诧异,这么真诚的笑。玩耍是她的幸福。 暑假到了,马上面临实习的哥哥回来了。可没过几天,就不见人影了,好容易盼他回来,暑假也结束了。他说他去了内蒙的好多地方。我关切的问他累吗?他说:累啊!随后又骄傲地说:“可是我学会了许多东西,我相信那对我以后的人生路是有帮助的。”我笑,大声地喊:哥,你是我的榜样。在他看来,他的暑假是充实的,他是幸福的! 夜幕降临,繁星点点。隔着一层帘,我看见常年劳作的父亲坐在那里,默默地吸着一支烟。灯光打在他的脸上,我看不清他的表情,只有那斑白的鬓角依稀可见。父亲真的老了,每天早出晚归来支撑这个家,他一定很累了。眼泪盈满了眼眶,最后还是不争气的流了下来……“咳、、咳、、”一阵剧烈的咳嗽声传来。我擦干眼泪,走到父亲旁边,父亲把那支烟熄灭,慈祥的笑笑,说:爸爸老了,不中用了。我说:没有啊!父女两开怀的笑了,笑声混着一个个烟圈飘向远方……我问父亲:爸,这么多年付出,这么多年劳作,你幸福吗?他坚定地告诉我,幸福!他说:“只要你们开开心心快快乐乐地成长,我做的一切都值得。”他又说:“霞,好好读书,爸爸赚钱供你上大学,我还没老呢,至少还能干XX年,20年……然后是一片寂静,我和父亲看着远方,那里有希望。 年迈的姥姥是家里的大长辈,他常常念叨:平安就是福。那也许是经历了人生的酸甜苦辣后的感悟吧!每逢新春,一大家人在姥姥家围着看电视时,那应该是她的幸福吧! 幸福是什么?它不是你一个人拥有一座豪宅,它是一家人在并不宽敞的屋子里谈笑风生。它不是你一个人有拥山珍海味,它是一家人和和乐乐的吃一些普通

值得学习的香港房地产模式

值得学习的香港房地产模式 “香港经验”依然值得内地同仁借鉴内地房地产业的改革发展与香港回归的脚步基本是同步的,这是历史的巧合,也是历史的必然。作为中国内地对外交往的重要窗口,“香港经验”一直是内地改革开放的重要样板。作为房地产而言,内地与香港在房地产所要面对的境况具有太多的相似,香港的发展思路也就成了以深圳为代表的众多内地城市的发展模式。 回归10年,内地与香港在交流中相互促进,在发展中互相借鉴,共同促进了经济的繁荣和发展。在房地产行业,房地产市场的10年与香港回归的10年基本重合。10年来,内地房地产市场化的发展处处显示出“香港经验”的印记。10年后,这些“香港经验”仍然值得内地房地产行业继续学习和借鉴。 香港房地产的发展,至少三个方面的经验都是内地房地产业界必须认真学习、研讨的重点。一是香港房地产业的快速起步和发展历史,二是公屋(廉租房)制度,三是香港处理亚洲金融危机所导致的房地产泡沫破灭的经验和智慧。 香港房地产的快速起步和发展,得益于自由完善的市场环境和灵活多样的融资体制,以及不断创新的对购房者进行支持的金融产品。房地产是一个资金密集型行业,而在香港房地产起步的上个世纪五六十年

代,无论是港府还是开发商资金都十分有限,楼花和按揭制度的创设和引入,使开发商能迅速回笼资金,大大提高了资金的使用效率,也引导了购房者的消费观念,而港府则通过土地招拍挂提高了财政收入。 这些措施对于起步阶段的香港房地产起到了重要的推动作用,这些制度也在改革开放后从深圳传入内地,促进了内地房地产的发展。随着时间的变迁,类似于预售制、招拍挂等内容也不断在实践中遇到问题,但是其基本思路,尤其是在提高资金使用效率方面的思路永远值得借鉴。 在内地,目前困扰房地产开发和银行系统的仍然是资金及其管理问题。由于投融资渠道单一,内地房地产开发资金70%左右直接和间接来自银行贷款,银行系统过多地承担了房地产金融风险,不仅为金融风险埋下隐患,而且使宏观调控处处掣肘。反观香港房地产,其融资渠道则顺畅得多,开发企业既可以从银行获得支持,也很容易通过发行股票和债券融资,而后者在内地基本属于起步阶段,仍然需要更多的政策支持。 香港的公屋制度起源于灾难性的“石硖尾大火”,公屋制度不仅包括政府出资建造建筑实体,还包括货币化的综援金制度。到1997年,在当时全港650万居民中,居住在出租公屋、政府补助出售单位的人口达331.38万,占全港人口的50.97%。公屋制度与香港的房地产大规模开发几乎同步,不仅解决了众多中低收入者的住房问题,还为香港节约

感受幸福作文(15篇)

感受幸福作文(15篇) 感受幸福作文第1篇: 幸福是什么?这是许多同学要问的问题。 很小的时候,我就明白钱能够买来一大盒巧克力;钱能够买来玩具汽车;钱能够买许多的美丽的洋娃娃;钱能够买来一个大楼…… 我以为有钱就是幸福。 倡我错了,钱虽然能够买来一屋子巧克力,但买了甜蜜,钱虽然能买到房子,可是却买来家庭幸福;钱虽然能买来药,可是却买来健康,钱虽然能买来闹钟,可是买来时间……那时,我又明白了有钱必须幸福。 以前,我总是为了一条连衣裙而朝思暮想,盼望有一天能够穿上裙子,去放风筝。那时候,我以为拥有就是幸福。 最终有一天,妈妈给我买了这条连衣裙,我高兴的一宿都没有睡觉。可是几天的新鲜劲没有了,穿上裙子后,我并没有什么改变,依然是一个黄毛丫头。于是把它扔到箱子里。几个月后,我又把它翻出来,可是已经小了,穿下了。我又明白了,虽然裙子很美,但都是暂时的,完美的时光总是转瞬消失。 “幸福是什么?”我依然没有感受到。 几年后,我在街上看到了一对耄耋老人,他们虽然履蹒跚,可是互相搀扶,有时抬头看看天上的云卷云舒,有时望望西天如血的残阳,她们脸上洋溢着的是满足和幸福。 噢,我明白幸福就是真情。虽然他们很穷,可是他们很

相爱。他们彼此珍惜,从感叹世界对他们的公平。往往有的有钱人,他们虽然很有钱,可是他们并幸福,因为他们的心总是被金钱和权势所占据了,根本享受了这天伦之乐。 幸福其实很简单,就是和爸爸、妈妈吃一顿饭,和他在一齐聊聊天。 感受幸福作文第2篇: 夜,悄悄地打开了黑暗,散布着一如既往的宁静,天上的繁星披上了闪装,正对着我的眼,似乎害怕我听到它们之间的悄悄话。 知何时,甘寂寞的虫儿起劲地奏起了动听的乐曲,清凉的微风夹杂着泥土的芳香悄悄地将白天的烦闷与喧嚣赶跑。夜,显得更加宁静而诗意了。 静静的,左思,右想,就这样静静地坐在楼顶上,感受着夜馈赠我的美妙。就连天上偶尔飘过的云朵,也像是怕惊动了夜的宁静,如绒毛在平静水面滑过般,显得那么轻柔而迷人。 今夜独处在空旷的夜空下,感受着夜带给我的美妙,幸福惬意溢满于心。原先自我一向以来苦苦追寻的幸福其实就在自我的身边。 以往,有人努力打拼,渴望生活富裕来获得幸福,可一辈子的艰辛拼搏使自我逐渐沦为金钱的奴隶,苦苦追寻的幸福也越寻越远,最终留给自我的是岁月无情地染白的头发。其实,幸福并非是追寻能得到的,幸福是一种感受,仅有用心感受身边的一切,你就能发现,幸福无处在,譬如,管贫

房地产公司的商业模式概述

房地产公司的商业模式 中城房网轮值主席、万通集团董事局主席冯仑:近期以来,业界各种各样的研讨会关注的不外乎三个层面的问题,第一是行业问题,即市场趋势,行业进展;第二是项目问题,产品性能,科技进步;在这两者之外,还有一层即公司问题。公司治理经营渐成大伙儿关注的重点,你那个公司如何能办得不仅今天赚钞票,而且能够持久进展,比较好地保持竞争力。我们通过一段时刻的考虑和研究,提出了房地产公司的商业模式,分成了几种类型,每一种类型我们会提出一些案例和一些典型的公司。 开发公司模式 1、房屋开发模式 该模式又分三种类型。 第一种类型为沃尔玛模式。比较典型的是万科模式,在不同城区的郊区大规模的拷贝,产品极其单一化,目标客户极其准确,体制上采取一个总部强势操纵,有打算地在郊区连锁开店,该模式经济增长特不快,万科今年营业额可能能够超过40亿元,会打破近五年来一个地产公司年销售额最高不超过30亿如此一个纪录。 第二种类型为百货公司模式。现在的华润置地是那个模式,即在同一个地域,各种产品同时做,产品多样化,像一个百货公司高中低档什么产品都有,商户、写字楼、住宅、酒店、公寓。这种百货公司模式比较多的见于过去城建系统转制过来的开发公司和国内专门多综合性的大型国营开发公司。

第三种类型为精品店模式。这是万通地产致力追求的模式,只在少数高端市场进行精品店经营,我可能卖的车是劳斯莱斯,一天卖不出几辆,然而每一辆的价格高,因此营业额较高。万通今年销售额会超过20亿元,要紧集中于高端产品。 2、土地开发模式 一种是陆家嘴模式,即一个整体公司以经营土地为主,通过规划,成片出让,同时与开发结合,要紧是综合金融、贸易、商业等业态。陆家嘴每年的营业额实际上专门少,但利润专门高,要紧是土地出让的收益特不大。 一种是天津开发区模式,即工业土地的开发模式,由于经营的土地要紧是工业区,都市机能较差,因此工业区土地价值的增值幅度和它收益情况比陆家嘴要差得多,但该模式也是国内惟一一个,甚至是要紧的一个靠土地经营的工业区赚钞票的一个企业。 3、混合开发模式 混合开发的模式又分成两种。一种是纵向重叠的混合开发模式,即现在传统的开发公司采取的模式,从拿地一直到物业治理纵向重叠起来,所有环节你自己都要做,如此功能上就不够专业化,公司内部治理上又互相重叠。在广东,甚至有相当多的企业还有自己的设计院、建材公司、施工建设公司。 另外一种,是交叉混合开发模式,典型案例是珠江和合生创展,该模式使拿土地和开发房子、建房子有适当的划分。珠江大片的拿地,然而合生创展几乎不自己拿地,只做房屋。如此交叉起来,同时又是一个老总,在北京、上海和广东有大量的开发,

相关主题