NBER WORKING PAPER SERIES
THE COMPETITIVE SAVING MOTIVE:
EVIDENCE FROM RISING SEX RATIOS AND SAVINGS RATES IN CHINA
Shang-Jin Wei
Xiaobo Zhang
Working Paper 15093
https://www.doczj.com/doc/7f17601188.html,/papers/w15093
NATIONAL BUREAU OF ECONOMIC RESEARCH
1050 Massachusetts Avenue
Cambridge, MA 02138
June 2009
The authors would like to thank Marcos Chamon, Avi Ebernstein, Lena Edlund, Roger Gordon, Ed Hopkins, Tatiana Kornienko, Justin Lin, Olivier Jeanne, Simon Johnson, Nancy Qian, Junsheng Zhang,and seminar participants at the NBER and various universities for helpful discussions, and John Klopfer,Lisa Moorman and Jin Yang for able research assistance. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research.
? 2009 by Shang-Jin Wei and Xiaobo Zhang. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including ? notice, is given to the source.
The Competitive Saving Motive: Evidence from Rising Sex Ratios and Savings Rates in China Shang-Jin Wei and Xiaobo Zhang
NBER Working Paper No. 15093
June 2009
JEL No. D1,F3
ABSTRACT
While the high savings rate in China has global impact, existing explanations are incomplete. This paper proposes a competitive saving motive as a new explanation: as the country experiences a rising sex ratio imbalance, the increased competition in the marriage market has induced the Chinese, especially parents with a son, to postpone consumption in favor of wealth accumulation. The pressure on savings spills over to other households through higher costs of house purchases. Both cross-regional and household-level evidence supports this hypothesis. This factor can potentially account for about half of the actual increase in the household savings rate during 1990-2007.
Shang-Jin Wei
Graduate School of Business
Columbia University
Uris Hall 619
3022 Broadway
New York, NY 10027-6902
and NBER
shangjin.wei@https://www.doczj.com/doc/7f17601188.html,
Xiaobo Zhang
International Food Policy Research Institute
2033 K Street, NW
Washington, DC 20006
x.zhang@https://www.doczj.com/doc/7f17601188.html,
”… [A] surge in growth in China and a large number of other emerging market economies … led to an excess of global intended savings relative to intended capital investment. That ex ante excess of savings propelled global long-term interest rates progressively lower between early 2000 and 2005.That decline in long-term interest rates across a wide spectrum of countries statistically explains, and is the most likely major cause of, real-estate capitalization rates that declined and converged across the globe, resulting in the global housing price bubble.” Alan Greenspan, Wall Street Journal, March 11, 2009
1. Introduction
High savings rates in certain countries are said to be a major contributor to the recent housing price bubbles and the global financial crisis by depressing global long-term interest rate in the last decade (Greenspan, 2009). The Chinese national savings rate, at about 50 percent of GDP in 2007, has caught special attention. This savings rate is high in at least three senses. First, it is higher than most other countries, including East Asian countries that are already known to have high savings rates. Second, it is higher than in China’s own past: the gross domestic savings rate as a share of GDP rose by about 15 percentage points since 1990. Finally, it is higher than China’s already-high investment-to-GDP ratio. China’s household savings are approximately half of its national savings. (In 2007, the household savings as a share of the household disposal income was 30%).
The purpose of this paper is to test a new hypothesis regarding household savings behavior using Chinese regional and household data. Before doing that, let us review existing explanations in the literature. The first is the life cycle theory (Modigliani, 1970, and Modigliani and Cao, 2004), which predicts that the savings rate rises with the share of working age population in the total population. This explanation doesn’t appear to be consistent with profile of savings at household level (Chamon and Prasad, 2008). The second explanation has to do with a precautionary savings motive in combination with a rise in income uncertainty, which is favored by Blanchard and Giavazzi (2005) and Chamon and Prasad (2008). The problem is that while both pension systems and the public provision of health care in China have been improved since 2003, household savings as a share of disposable income rose sharply during the same period. This time series pattern contradicts the precautionary motive theory. The third explanation is a low level of financial development. This has the same difficulty as the last explanation since the financial system is most likely more efficient today than a few years ago yet the
savings rate still rose. The fourth explanation is cultural norms. But cultural norms tend to be persistent, and therefore are unlikely capable of explaining the visible rise in the savings rate over the last two decades1.
In this paper, we suggest that an alternative competitive saving motive may be at work: families with sons compete with each other to raise their savings rate in response to ever rising pressure in the marriage market. Competitive saving by these families spills over to greater savings by other families, possibly through raising the prices of non-tradable goods such as housing. The increased pressure in the marriage market comes from China’s rising sex ratio imbalance, which has made it progressively more difficult for men to get married. As far as we know, we are the first in the literature to propose this hypothesis as an explanation for a rising savings rate in China. Toward the end of the paper, we argue that the explanation is likely applicable to many other countries as well.
We provide a series of evidence. First, across provinces, we show that the local savings rate tends to be higher in regions and years in which the local sex ratio (for the pre-marital age cohort) is higher. This continues to be true after we control for local income, social safety net, the age profile of the local population, and province and year fixed effects.
Second, in recognition of possible endogeneity of and measurement error in local sex ratios, we employ instrumental variables where the local sex ratio for the pre-marital age cohort is shown to be linked to local financial penalties for violating family planning policies set more than a decade earlier (as Ebenstein, 2008, and Edlund et al, 2008, also document). With two-stage least squares estimation, the effect of local sex ratios on local savings rates remain positive and statistically significant. In fact, the point estimate
1 We do not study corporate savings behavior in this paper. The Chinese corporate savings rate has risen sharply in recent years, accounting now for about half of the national savings rate (Kuijs, 2006). The corporate savings behavior is a separate puzzle to be explained. The existing explanation suggests that a combination of state-ownership and windfalls in resource sectors is the primary driver. (The government savings rate is relatively moderate and has turned negative in 2008-09.) We note, however, that a recent paper by Bayoumi, Tong and Wei (2009) discusses China’s corporate savings rate in a global context and casts doubt on the usual interpretation. Because corporate savings rates have been rising globally (Bates, Kahle, and Stulz, 2005; and IMF, 2005), it turns out that the Chinese corporate savings rate is only modestly higher than those of other countries (by
2 percentage above the global average savings rate when comparing listed companies across countries). So differences in corporate savings are unlikely to be a big part of the cross country differences in national savings rates. Moreover, comparing corporate savings by Chinese firms of different ownership, in resource and non-resource sectors, Bayoumi, Tong and Wei (2009) do not find evidence that state-owned firms save more than private firms, or that the corporate savings rate is unusually high in resource sectors. This casts doubt on the notion that a high Chinese corporate savings rate is mainly a result of poor corporate governance and inefficiencies tied either to state-ownership or to windfalls in resource sectors.
becomes larger. This suggests that an increasing imbalance in the sex ratio causes a rise in the savings rate.
Third, we examine household data using household surveys that cover 122 rural counties and 70 cities. While households with a son typically save more than households with a daughter, we do not regard this per se as supportive evidence of our hypothesis, since other channels could account for this difference. Instead, the evidence that we find compelling is that savings by otherwise identical households with a son tend to be greater in regions with a higher local sex ratio. This is something clearly predicted by our hypothesis, but not by any other existing explanations. In addition, we find that savings by households with a daughter do not decline in regions with a high sex ratio, which is consistent with our interpretation that the savings pressure on households with a son spills over to other types of households. We discuss reasons that these patterns at the household level are unlikely to be the outcome of some selection in the data.
Finally, we provide several supplementary pieces of evidence. We show that local housing values indeed tend to be higher in regions with a higher local sex ratio, even after taking into account local income. This is direct evidence that the competitive pressure on households with a son in the marriage market may trigger other households to save more just to cope with higher local housing costs. We also provide some evidence that household level savings rates tend to be linked to a wedding event in a family in a quantitatively significant way, and that a groom’s family tends to save more than a bride’s family in preparation for the wedding.
We do not wish to claim that no combination of the existing explanations could contribute to a higher savings rate. Instead, we suggest a competitive saving motive as an additional explanation. The estimated effect of a rising sex ratio on the Chinese savings rate is economically significant, and can be projected to become even more important in the foreseeable future. Based on the point estimate (0.74) in the IV regression, a rise in the sex ratio for the pre-marital age cohort from 1.05 to 1.14 (which is actual increase in Chinese sex ratio for the age cohort of 7-21 from 1990-2007) would lead to a rise in the savings rate by 6.7 percentage points, which is 48% of the actual increase in the household savings rate. If we run separate regressions for rural and urban areas, we find that the elasticity of the local savings rate with respect to the local sex ratio is larger in
rural areas than in urban areas. The increase in the rural sex ratio is estimated to account about 53% of the actual increase in the rural savings rate from 1990 to 2007.
Because the sex ratio imbalance at birth has been increasing steadily since mid-1980s, the imbalance for the pre-marital age cohort will almost surely be higher over the next decade than in the last decade, even if the sex ratio at birth starts to be reserved soon. This implies that the incremental savings rate that is stimulated by the competitive savings motive will almost surely rise in importance in the near future.
A high savings rate in a large economy is a significant contributor to global current account imbalances. Once one recognizes that the sex ratio imbalance is a structural factor behind a rising savings rate, it should be clear that a discussion of global imbalances that focuses narrowly on exchange rates or even social safety nets is incomplete. Furthermore, policy actions that improve the economic status of women could potentially reduce the sex ratio imbalance by reducing parental preference for sons (Qian, 2008). A change in the family planning policy that relaxes birth quotas could also reduce the imbalance. Because of their important implications for aggregate savings and current account imbalances, these changes deserve more attention that they receive now.
The paper is organized in the following way. In Section 2, we develop the argument more fully, lay out some caveats and possible answers to them, and make connections to related literatures. In Section 3, we provide statistical evidence for our hypothesis. Finally, in Section 4, we conclude and discuss possible future research. A data appendix explains the sources and definitions of the main variables, including measures of sex ratio imbalance and of savings rates.
2. Developing the argument: unbalanced sex ratios and competitive savings
In this section, we first document the evolution of the sex ratio imbalance in the Chinese society over the last three decades. We then explain why this could trigger a race to raise savings rate, and connect this discussion to related literature.
From unbalanced sex ratios to “bare branches”
Left to the nature, the sex ratio at birth (in a society without massive starvation) is generally around 106 boys per 100 girls (with human biology compensating for a slightly
higher mortality rate for infant boys than girls). The sex ratio was balanced or slightly below normal in the 1960s and 1970s (mostly likely due to malnutrition). The sex ratio at birth in China was close to be normal in 1980 (with 106 boys per 100 girls), but climbed steadily since the mid-1980s to over 120 boys for each 100 girls in 2005 (Li, 2007; Zhu, Lu, and Hesketh, 2009) and estimated to be 124 boys/100 girls in 2007. By 2005, men outnumbered women at age 25 or below by about 30 million. The excess men cannot be married mathematically. The number of unmarried men -sometimes referred to as “bare branches” in colloquial Chinese - continues to rise as the sex ratio imbalance deteriorates2.
Some men may partner off as gays, and others may emigrate or marry women from other countries. Because the scale of the “bare branches” is so large – 30 million men are more than the entire male population of Italy or of many other countries, and because most “bare branches” come from low income households, actions by a small portion of men do not provide a practical solution to the problem. In any case, a rising sex ratio imbalance must imply a diminishing probability that a man will find a bride3.
From fear of becoming a “bare branch” to competitive savings
Most men have a desire to get married. It may be safer to say that, in an Asian society, parents of a son strongly prefer for their son to be married. As the competition
for a dwindling pool of potential wives intensifies, the parents of a son (or a son himself) will try harder to improve the son’s prospects for marriage. Postponing consumption and raising the household savings rate is one such action that families may take. To be successful, a family needs to save more than enough number of other competing families. If all families think the same way, this leads to competitive saving. (Of course, in general
2 If some new-born girls are not reported by their parents with hopes to be pregnant again with a son, then the sex ratio imbalance at birth could be overstated in official statistics. To assess the quantitative importance of this possibility, we compare the sex ratio at birth in the 1990 population census with the sex ratio for the 10 years old in the 2000 census. It is reasonable to assume that parents would not hide their 10-year old girls from census-takers in 2000. First, those parents who would like to try for another child in 1990 most likely would have done so already within ten years, and have paid a fine for violating family planning policy by 2000. In addition, there were also positive incentives to report the girls who have reached school age since registration was required for (free) immunization shots and school attendance. Since the sex ratios for both the new-borns in 1990 and the 10 years old children in 2000 were 1.12, we conclude that the under-reported infant girls, as a proportion of total number of new-born girls, are not large enough to make a noticeable distortion to reported sex ratio imbalance. Zhu. Li and Hesketh (2009) reached the same conclusion with a somewhat different methodology.
3 A fraud has recently emerged in which some women pretend to be willing to marry bachelors in a rural area in return for a bride price (“cai li”) on the order of RMB 40,000 (about US$5900, or “five years’ worth of farm income”). The women would then run away after the wedding with the bride price (“It’s cold cash, not cold feet, motivating runaway brides in China,” by Mei Fong, Wall Street Journal, June 5, 2009)
equilibrium, the total number of unmarried men will not be changed by household savings decision. But an individual family’s desire to improve marriage prospects for its son may lead all families with a son to compete to increase their savings.]
The idea that accumulating more wealth may improve one’s chance in the marriage market is not unique to China. For example, pop star Madonna has declared in the hit song, “Material Girl,” that: “We are living in a material world/ and I am a material girl/Some boys try and some boys lie but/ I don’t let them play/ Only boys who save their pennies/ make my rainy day.” So she sees a connection between a man’s savings rate and his success in dating. To be clear, our hypothesis does not require women to be material girls (in China or elsewhere). Indeed, other factors can be important for success in finding a spouse. But other things being equal, as long as more wealth improves a man’s likelihood for marriage, parents with a son (or a son himself) will be encouraged to raise their savings rates. Many factors (such as health and appearance) are difficult to control, but the savings rate is one such thing that parents or men themselves can act on. However, we are not saying that the savings behavior is the only variable that is altered by a rising sex ratio. Instead, parents with a son may do all things in their power to improve their son’s marriage prospect, including perhaps investing more in their son’s education, and pushing him to work harder. The hypothesis in the current paper is that postponing parents’ consumption and raising their savings rate may be one such variable that responds positively to a rising sex ratio.
For the sex ratio to affect household savings rates, parents don’t have to know local sex ratio statistics. There is an invisible hand at work. Consider two otherwise identical households with a son, one in a region with a high sex ratio, and the other in a region with a low sex ratio. Parents in the first region would observe or be told by relatives or colleagues with a son that it is very expensive for their sons to find a girlfriend and to marry. The expectation for how much the parents (or the sons) need to contribute to their son’s new household, given costs of housing, cars, furniture, or honeymoons, would differ in the two regions. The types of furniture, cars and honeymoons, and local housing prices may already reflect the degree of competition in a local marriage market, and thus affect the savings required of parents with a son. In other
words, even without knowledge of local sex ratio statistics, parents with a son may make savings decisions that reflect the local sex ratio.
The initial inspiration for the hypothesis comes (from our visits to the National Zoo in Washington DC, and) from the literature on evolutionary biology. In nature, male sea lions or walruses tend to be physically larger than corresponding females; in fact, this pattern holds for most species. A leading hypothesis for why this occurs, sexual dimorphism, conjectures that because bigger and stronger males have an advantage in competing for and retaining females, differences in size are reinforced over time by natural selection (Weckerly 1998). It is likely that humans had to do the same a long time ago; that is why men, on average, are somewhat taller and larger than women. By now, the (sexual) returns to progressively larger males are much lower, if not negative. Men may discover that possessing a larger house, a bigger savings account, and more general wealth is a more effective mating strategy.
Existing literature, potential caveats, and counter-arguments
No other paper in the existing empirical literature that we are aware of makes a connection between sex ratios and savings rates. Nonetheless, a relevant economics literature is the work on status goods, positional goods, and social norms (e.g., Cole, Mailath and Postlewaite, 1992; Hopkins and Kornienko, 2004 and 2009). When allowing certain goods to offer utility beyond their direct consumption value (i.e., through “status,” which in turn could affect the prospect of finding a marriage partner), it is easy to show that consumption and savings behavior can be altered. It is important to point out, however, that the effect of a rising sex ratio imbalance on savings rates is conceptually ambiguous. In particular, when competition in the marriage market increases, men (or their parents) may compete by increasing their conspicuous consumption, if conspicuous consumption effectively signals their attractiveness; this would result in a decline in the savings rate. Our response is that, while conspicuous consumption may increase the frequency of dating, the probability of securing a marriage partner may depend more on showing substantial wealth than on showing off a few flashy goods. Furthermore, a visible way to demonstrate a man’s desirability is by owning a larger house (at least in a developing country like China), which requires a larger savings before the purchase is
made than otherwise. Both signaling strategies can induce households with a son to raise their savings rate. In any case, it is an empirical question as to whether savings rates are positively or negatively related to sex ratio imbalances.
The theoretical models in Hopkins (2009) and Hopkins and Kornienko (2009) could be interpreted to predict that a rise in sex ratio imbalances leads to a rise in savings rates. In a possible reading of their models, men compete for potential wives through effort (including by raising their savings rate). Assume that the reward for a higher savings rate is a better chance to win a wife. Men with the lowest savings rates, on the other hand, may not find a wife. As the fraction of men who may stay unmarried increases, men (without coordination) compete by saving more. The resulting level of savings for men is inefficiently high: if all men were to cut their savings by the same amount, the chance for each of them to be matched with a wife would stay the same, but they would have avoided postponing consumption unnecessarily.
When the savings effect dominates the conspicuous consumption effect for parents with a son (or unmarried men), would parents with a girl (or unmarried women) save less since a rising sex ratio is a favorable development for them? Indeed, could the reduction in their savings be so much as to completely offset the increase in savings by parents with a son or unmarried men? In a way, we can wait for the data to tell us the answer. Here, it is useful to point out the existence of an opposing force that could potentially raise the savings rate even by parents with a daughter. That force is the price of housing. Parents with a son (or unmarried men) may attempt to increase their competitiveness by buying a larger house, and may bid up housing prices in a region with an unbalanced sex ratio. As a consequence, even parents with a daughter have to save more in order to afford housing. This is a spillover effect4.
This discussion has clear implications for the empirical work. First, we need to estimate the net effect of higher local sex ratios on local savings rates. Second, it would be useful to check how savings by households with a son or with a daughter respond to local sex ratios. Third, it would be informative to check if local housing prices are indeed linked to local sex ratios (holding constant other factors).
4h When all men save more, the reward for savings by women or parents with a daughter increases, if wealthier men also prefer relatively wealthy women. As a result, parents with a daughter are also more willing to save. For a theoretical model that may deliver this result, see Peters and Siow, 2002. This could be an additional spillover channel.
Determinants of sex ratio imbalance
Sex ratio imbalance comes almost entirely from sex selective abortions. This, in turn, results from a combination of three factors: (a) parental preference for sons; (b) some limit to the number of children a couple is allowed or wants to have, which for the Chinese is a strict family planning policy; and (c) availability of inexpensive technology to screen the sex of a fetus (Ultrasound B in particular) and to perform abortions.
Our empirical work will start with regressions that assume exogenous sex ratios. This assumption can be justified by recognizing that parental preference for sons is part of a culture, and as such, it changes only very slowly. Korea has experienced a sustained increase in its sex ratio imbalance for about 25 to 30 years, which has only recently started to decline; this evidence is consistent with our assumption (Guilmoto, 2007).
We nonetheless also report instrumental variable regressions that allow for potential endogeneity of (and measurement error in) sex ratios. The instrumental variables for sex ratio in the pre-marital age cohort explore regional variations in the financial penalty for violating birth quotas, set by regional governments years before newborns grow to marriageable age.
3. Statistical Evidence
Since 1980, both the sex ratio for marriage-age youths and the savings rate in China have been rising. In Figure 1, we present a time series plot of standardized versions of both variables,5 with the sex ratio at birth lagged by twenty years. The sex ratio is lagged since the median age of first marriage for Chinese women is about 20. The two standardized variables, visually, are highly correlated (the actual correlation coefficient is 0.822). While this is highly suggestive, it is not a rigorous proof by itself.
Panel regressions across Chinese provinces during 1980-2007
We start by examining provincial-level data for any association between local savings rates and local sex ratios. We perform a panel fixed effects regression that links a
5 standardized variable = (raw variable – mean)/standard deviation.
location j’s savings rate in year t with the sex ratio for the appropriate age cohort in that same location and year, controlling for location fixed effects, year fixed effects, and other factors. To be precise, our specification is the following:
Savings_rate j,t = β Sex_ratio j,t +X j, tΓj,t + province fixed effects + year dummies +e j,t
Following Chamon and Prasad (2008), we define the local savings rate by log (income net of taxes / living expenditure).6 This definition is less susceptible to extreme values, and makes the error term more likely to satisfy the normality assumption. We cluster the standard errors by province.
Ideally, we would like to know sex ratios for a fixed age cohort in every region and in every year. However, such data are not available as the Chinese population census is carried out only once every few years (in 1982, 1990 and 2000). Moreover, only the 2000 census offers public data for individual age groups at the provincial level. Given these constraints, we make the following short cut: we focus on the sex ratios for the age cohort 7-21 in all years, inferred from the 2000 population census. For the age cohort 7-21 in 2007, we infer their sex ratio from the age cohort 0-19 in the 2000 census, since the two groups should theoretically be the same. Similarly, for the age cohort 7-21 in 1990, we infer their statistics from the cohort 17-31 in the 2000 census; and so on.
A caveat with this method is that the actual sex ratio is likely to be different from the inferred one for all years other than 2000. In particular, because the mortality rates for boys and young men are generally slightly higher than those for girls and young women, we may under-estimate the true sex ratios for years before 2000 and over-estimate them for years after 2000. However, under the assumption that measurement errors are common across all regions in any given year (but may vary from year to year), we can eliminate the effect of measurement errors by including year fixed effects in regressions.
As control variables, we include both log income and proportions of the local population in the age brackets of 0-19 and 20-59, respectively. Table 1a presents the summary statistics of the major variables used in the provincial level analysis. Table 1b
6 Income and expenditure data, which are aggregated based on nationwide rural and urban household surveys, are from various issues of China Statistical Yearbooks.
lists the outlier provinces – those with the highest and lowest sex ratios in various years. For example, in 2005, Jiangxi and Shaanxi had the highest sex ratios at birth, both in excess of 130 boys per 100 girls. At the other end of the spectrum, Tibet, Liaoning, Jilin, and Xinjiang had the lowest sex ratios at birth, with 109 boys or less per 100 girls.
In Column 1 of Table 2, we report regression results with only sex ratio, income and population shares for two age groups as the regressors (plus province and year fixed effects). The effect of local income on local savings rates is positive: a one percent increase in local income is associated with local savings rate 0.26 percentage points higher. The coefficient of local sex ratio (for the age cohort 7-21) is 0.39 and statistically different from zero at the 5% level. In other words, the local savings rates tend to be higher in regions with a more imbalanced sex ratio.
The age profile of local populations produces some puzzling patterns. In contrast to the prediction of the life cycle hypothesis, the share of working age population (the age cohort of 20-59) has a negative coefficient. This means that old-age households and households with children save more than do households in between. We note that this is consistent with the notion that parents save more when they have children, and that old people save more either because they have a strong bequest motive, or because they realize their financial need in the old age is greater. Regardless of these explanations, we note that similar patterns are documented in Chamon and Prasad (2008).
The existing literature has hypothesized that rising income and job uncertainty is what motivates the Chinese to save more. In Column 2, we use the proportion of local labor force that work for state-owned firms or government agencies as a proxy of the degree of job security. Under the precautionary savings hypothesis, the savings rate should decline with better job security. The coefficient indeed has a negative coefficient (-0.14); however, it is not statistically significant. In any case, the coefficient on sex ratio is still positive and significant. The point estimate (0.70) is now substantially larger.
Because men and women may both have different savings rates and different income levels, one might worry that income inequality could affect local savings rates directly, and that a sex ratio imbalance is simply a proxy for earnings inequality. For a subset of provinces and years, we can measure local income inequality directly by the
Gini coefficient.7 In Column 3 of Table 2, we add the local Gini coefficient as an additional control. While the coefficient is positive – consistent with the idea that a greater inequality is associated with a higher savings rate, it is not statistically different from zero. With this much reduced sample, the coefficient on the local sex ratio is still positive and statistically significant. The point estimate jumps to 0.92.
In Column 4 of Table 2, we include local life expectancy as an additional regressor to account for the possibility that households save more when they expect to live longer.8 We also the share of local labor force enrolled in social security as a proxy for the extent of local social safety net. Neither coefficient is statistically different from zero.This suggests that inadequacy of social safety net does not appear to be as quantitatively important in explaining savings rates as commonly believed. We make this observation with one important caveat: this does not rule out the possibility that every region’s saving rate has been made higher due to a poor national social safety net.
Caroll, Overland, and Weil (2008) point out that, assuming habit formation in consumption, savings rate should tend to be higher in a fast-growing economy since consumption growth may not catch up with income growth immediately. In the last column of Table 2, we add the local growth rate of the preceding five years. This variable turns out to be insignificant, and the point estimate is in fact negative, which would have been consistent with a more standard model of consumption smoothing without habit formation. In any case, the coefficient on local sex ratio is still positive (0.34) and statistically significant. Across the columns in Table 2, the positive association between a high local sex ratio and a high local savings rate is robust and statistically significant.
Rural versus urban areas
Urban and rural areas differ in income, education level, and coverage of social safety nets. Parental preference for a son is also known to be stronger in rural areas. Perhaps most importantly, local marriage markets may work differently in rural and urban areas. A majority of marriages in rural areas take place between a man and a
7 The Gini coefficients are obtained from Ravallion and Chen (2007). The data are available for 29 provinces in 1988, 1990 and 1993, and 28 provinces in 1996 and 1999 for the urban sample, and 27 provinces in 1988, and 28 provinces in all other years for the rural sample. The overall Gini coefficients at the province level are approximated by weighted average of rural and urban Gini coefficients.
8 Life expectancy at the provincial level is only available in the three census years (1982, 1990 and 2000).
woman from the same county9. Most migrant workers either get married before leaving their homes to work in a city, or return to their villages to get married. In comparison, it is somewhat more common for marriages in cities involving a husband or a wife from outside the city. An implication of this difference in the marriage market is that the same local sex ratio imbalance may exert a smaller competitive pressure on men in a city than in a rural area. For these reasons, one may expect local savings rates to be more sensitive to local sex ratio imbalances in rural areas than in urban areas. Therefore, additional confirmation of the hypothesis may be obtained by running separate regressions for these two areas. The control variables are the same as those in Table 2 to the extent they are available for separate rural and urban areas.
The results are reported in Table 3. It is interesting to note that the estimated elasticity of local savings rates with respect to sex ratios is indeed greater for rural areas than for urban areas (0.75 versus 0.36, respectively, from Columns 2 and 4 of Table 3).
Instrumental variable regressions
The degree of a local sex ratio imbalance for the pre-marital age cohort (7-21) is pre-determined with respect to local savings decisions by construction, since the sex ratio is determined by parental decisions -- whether to undertake a sex selective abortion before a child is born -- taken many years prior to the corresponding savings variables in the regressions. This helps to justify the panel regressions reported in Tables 2 and 3. Nonetheless, one has to think hard about the possibility that sex ratio is endogenous, or that sex ratio is a proxy for something else that affects savings decision directly. For example, factors that affect sex-specific earnings in a region could simultaneously determine both a preference for sons and household savings decisions. In addition, as we noted earlier, local sex ratios may be measured with errors since they are inferred from the 2000 population census. In either case, the estimated elasticity of the local savings with respect to the local sex ratio may be biased.
A solution to both the endogeneity issue and measurement errors is to employ an instrumental variable approach, which we turn to now. A key determinant of the sex ratio
9 According to the China Population Census 2000, about 10% of people migrate to places outside their registered counties or districts in 2000. Among them, only 2.5% list marriage or family reunion as a major reason of migration.
imbalance is a strict family planning policy introduced in the early 1980s.10 We explore two determinants of local sex ratios that are unlikely to be affected by local savings rates, and for which we can get data. First, while the goals of family planning are national, the enforcement is local. Eberstein (2008) proposes to use regional variations in the monetary penalties for violating the family planning policy as an instrument for the local sex ratio. Using data collected by Scharping (2003) and extending them to more recent years, Eberstein focuses on two dimensions of penalties: (a) a monetary penalty for the violation of policy, expressed as a percent of annual income in the province, and (b) a dummy for the existence of extra penalty for having higher order unsanctioned births (e.g., for having a 3rd child in a 1-child zone, or for having a 4th child in a 2-child zone). These two variables are part of our set of instruments too. Second, while the Han ethnic groups faces a strict birth quota, the rest of the population (i.e., the 50 some ethnic minority groups) do not face or face much less stringent quotas. (The government allowed the exemption, possibly to avoid criticisms for using the family planning policy to marginalize minority groups). Since non-Han Chinese are not uniformly distributed across space, this variation offers one more possible instrument (Bulte, Heerink and Zhang, 2009).11
In Table 4, we report the first-stage regressions for the IV regressions that link local sex ratios to their determinants, with both financial penalties and minority shares lagged by 14 years (to match the median birth year for the age cohort 7-21). Both types of variables appear to be related to sex ratios. First, more severe financial penalties -- set in a decade earlier -- are indeed associated with a more unbalanced sex ratio. Second, the proportion of people not subject to birth quotas is negatively related to local sex ratio imbalance. The adjusted R-squared for the first-stage regressions is in excess of 60%.
In Column 1 of Table 5, we report the 2SLS estimation results for local savings rates where the local sex ratio is instrumented by the three variables described above.
10 China’s family planning policy, commonly known as the “one-child policy,” has many nuances. Since1979, the central government has stipulated that Han families in the urban areas should normally have only child (with some exceptions). Han Chinese are in the majority ethnic group, accounting for about 95%of the Chinese population at the time the policy was introduced. Families in rural areas can generally have a second child if the first one is a daughter (this is referred to as the “1.5 children policy” by Eberstein, 2008). Ethnic minority (i.e., non-Han) groups are generally exempted from birth quotas. Non-Han groups account for a relatively significant share of local populations in Xinjiang, Yunnan, Ganshu, Guizhou, Inner Mongolia, and Tibet.
11 In principle, variations in the cost of sex screening technology especially the use of an Ultrasound B machine, and the economic status of women (such as that documented in Qian 2008) could also be candidates for instrumental variables. Unfortunately, we do not have the relevant data. Note, however, for the validity of the instrumental variable regressions, we do not need a complete list of the determinants of local sex ratio in the first stage.
While a Durbin-Wu-Hausman test rejects the null that the sex ratio is exogenous (with a p-value of 0.03), a Hansen’s J statistic for over-identification fails to reject the null that the instrumental variables are valid (with a p-value of 0.30). With the 2SLS procedure, the local sex ratio continues to have a positive coefficient that is statistically different from zero. The point estimates, 0.74, is in fact larger than most corresponding estimates
in Table 2. This suggests that an attenuation bias from measurement errors might have outweighed an endogeneity bias in the original panel regressions. Based on the point estimate in Column 1 (0.74), an increase in the sex ratio for the age cohort 7-21 from
1.045 in 1990 to 1.136 in 2007, leads to a rise in the savings rate by 6.7 percentage points, accounting for 48% of the actual increase in Chinese savings rate during this period (details of the calculation can be found in Table 5a).
We also find that richer regions save more. A one percent higher per capita income is associated with a higher savings rate by 0.27 percent. Regions with more people working in the state sector save less. An increase in the share of state sector employment in local population by one percentage point is associated with a reduction in local savings rate by 0.24 percentage points. The last finding supports a precautionary savings motive: If more public sector employment implies less income and job uncertainty, then there is less need to save. We do not find evidence that the age profile
of the local population matters per se, which suggests that the life cycle hypothesis is not supported in the data (as in Chamon and Prasad, 2008).
In Column 2 of Table 5, we replicate the 2SLS estimation but excluding the share of minorities in local population from the set of instruments. Even though the Hansen’s J test in the first column suggests that all three instrumental variables, including the minority share, are valid in a purely statistical sense, we act conservatively here and allow for the possibility that non-Han Chinese have a different desired rate of savings and thus should not be in the set of instruments. In this case, the local sex ratio continues to exhibit a positive and statistically significant coefficient, with the point estimate becoming even larger (0.89). An increase in the sex ratio for the age cohort 7-21 from 1.05 in 1990 to 1.14 in 2007, would now lead to a rise in the savings rate by 8.0 percentage points (=0.09 x 0.89 x 100), accounting for 50% of the actual increase in Chinese savings rate ( =6.66/[(0.31-0.15)x100] ). With household level regressions to be
reported later (Tables 7-9), we find no robust evidence that savings by households headed by ethnic minorities behave differently from their Han counterparts in a given location. In other words, minority shares are unlikely to affect savings rates directly without going through local sex ratios. Therefore, we prefer those 2SLS estimates in Column 1 in which all three instruments are used.
In Columns 3 and 4 of Table 5, we apply the three instruments for sex ratio to
2SLS estimation where the dependent variable is either the rural or the urban savings rate. We confirm the results in the earlier panel regression: a higher local sex ratio raises local savings rates in both areas. The reaction of the local savings rate to a change in the sex ratio is stronger in rural areas. An increase in the rural sex ratio from 1.048 to 1.141 (the actual mean increase from 1990 to 2007) would lead to an increase in the rural savings rate by about 6.6 percentage points, or about 53% of the actual increase in the savings rate during this period12. For the urban areas, an increase in the sex ratio from 1.037 in 1990 to 1.113 in 2007 would raise the savings rate by 4.6 percentage points, accounting for about 26% of the actual rise in the savings rate. (Table 5a presents the calculations).
Household-level evidence
It is useful to go beyond regional aggregate comparisons and look at evidence at the household level. From data in the Chinese Household Income Project (CHIP) of 2002, which covers 122 rural counties and 70 cities,we construct a sub-sample of households with one or two children and a household head younger than 40.13Since most unmarried young people live with their parents, the survey does not contain many observations of an unmarried young man or woman as the household head. Therefore, we are not able to analyze such households directly.
One may be tempted to compare savings rates for households with sons and those with daughters. But this comparison is not particularly informative for our hypothesis. Under the hypothesis of a competitive saving motive, one expects that families with a son
12 In the rural savings equation, it is useful to note that the Durbin-Wu-Hausman test does not reject the null that the sex ratio regressor is uncorrelated with the error term in the original OLS (panel) regressions in Table 3. In this case, one may prefer the estimates in Columns 1-2 of Table 3 on the efficiency ground. (At it turns out, the Hansen’s J test in Table 5 suggests that the IV’s do not work well for the rural savings regression.)
13 We place an age limit of 40 for heads of households with an aim to exclude households with some older children (who have left home) and some younger ones. They may not be comparable to households with only younger children.
to save more, if other things are held constant. However, other things cannot be held constant because parents may not expect to get the same degree of help from their daughters than from their sons as they age, especially in a rural area where a woman moves to live with a man’s family after the marriage. In other words, families with only daughters may need to save more to prepare for old age. For this reason, a direct comparison of the savings rates between these two types of households is not informative for our purpose.
In any case, Table 6 reports average saving rates for households with children of different genders. In both rural and urban areas, households with a son have a moderately higher savings rate than those with a daughter (37% versus 33% in rural areas, and 30% versus 26% in urban areas). However, none of the differences in savings rates is statistically significant; the standard deviation of the savings rate within any type of household easily overwhelms the difference in the savings rate between any two types of household. Of course, large standard deviations also suggest the presence of considerable noise in the savings data. In any case, we cannot confirm or reject our hypothesis by comparing the savings rates across household types in this way.
Our hypothesis, however, implies a particular regional variation in saving rates: households with a son should save more in a region with a more unbalanced sex ratio, holding constant family income and other characteristics. Moreover, this pattern is not predicted by either the life-cycle theory or by existing precautionary savings motive hypotheses. Therefore, examining the relationship between household savings rates and local sex ratios may be particularly informative for testing our hypothesis.
We can also examine the relationship between the savings rate by households with a daughter and the local sex ratio. This helps us to check the presence of a spillover channel in savings pressure from households with a son to other households. If the spillover channel operates through housing prices, it is likely to be stronger in the urban areas as houses are more likely to be purchased from the local market (as opposed to being built on the occupants’ own land in rural areas).
The regression results for the rural sample are presented in Table 7. The first four regressions are performed on a full sample. The last four regressions are on a sample where the top and bottom 5% of savings rate outliers are removed. Since the large
standard deviations in the savings rates reported in Table 6 likely reflect noise, we place more trust in the results from regressions where the outliers are removed. We therefore focus our discussion on the results reported in the last four columns of Table 7. (The results from the first four columns largely confirm the same patterns.) The regressions control for family income, children’s ages, characteristics of the head of household (sex, education, and ethnic background), and local income inequality. It also controls for health shocks to the family by a dummy denoting “poor health” if the family has a disabled or severely ill member.
Column 5 of Table 7 relates savings by households with a son to local sex ratios and other determinants of savings rate. We find that the local sex ratio has a strongly positive effect on the household savings rate. An increase in the local sex ratio from 1.05 to 1.14 (the mean increase in rural China from 1990 to 2007) is associated with a higher household savings rate by 12.2 percentage points, which is economically large. In comparison, Column 6 of Table 7 reports the regression concerning savings by households with a daughter. The coefficient on the local sex ratio is negative (-0.05), consistent with the possibility that households with a daughter take advantage of a higher sex ratio imbalance in their favor by saving less. (Surveys of rural households in Guizhou province of China conducted by one of the authors in 2005 and 2007 show that a bride’s family often expects a financial transfer from a groom’s family). However, the coefficient is statistically insignificant. This may reflect an offsetting effect from a spillover in the savings pressure that we have discussed.
In Columns 7 Table 7, we report a regression on savings by households with two daughters. The coefficient on local sex ratio is more negative in this case (-0.36) than in the one-daughter case (-0.05). This is consistent with the notion that a higher sex ratio imbalance per se raises the bargaining power of the families for every daughter they have. However, the coefficient is still statistically insignificant, possibly reflecting a strong offsetting effect from the spillover of competitive savings by families with a son.
In Columns 8 Table 7, we report a regression on savings by households with a son and a daughter. (It is relatively uncommon in the sample to have two sons due to the family planning policy). The coefficient on the local sex ratio is positive (0.16),
高一正能量作文800字【三篇】 【篇一】 这句是很有哲理的话，分享给大家：对于人来说、的快乐、的幸福、是把自己的精神力量奉献给别人。 我愿意做赛场上鼓掌的那个人，将爱与支持奉献于一路奔跑的人们，成为支持力量的那种力量存在。如孟子和岳飞的母亲指引给孩子正确的人生方向;如海伦凯勒的家教沙利文给予其精神力量让她不惧黑暗;如擅使计谋的军师诸葛亮鞠躬尽瘁死而后已。 “选择你所喜欢的，爱你所选择的”每个人的人生态度都不一样，选择的方向也不同，而我选择鼓掌，则是一种人生要为之不断奋努力的方向和目的。 “应该让别人的生活因为有了你的存在而更加美妙”，鼓掌者，心存善与美，心灵芳香，成为人们心灵的驿站。1942年德军的铁蹄踏碎了巴黎的宁静，花店的老板洛希亚担忧战争让热爱生活的巴黎人沉入黑暗与恐惧不能自拔，于是在夜里为城镇里的左领右舍每家送了一大束玫瑰。第二天，几乎全巴黎的女士都捧着玫瑰走在街上，家园的美妙让远方的战士们受到了极大的鼓励，这就是的“玫瑰花的早晨”。洛希亚那鼓励人们热爱生活的掌声，回响在巴黎的黑暗年代里，在每个听到的人们心里，培育出芬芳的玫瑰，植根于精神世界里，永不凋谢。而这，也正是我所努力的目的与动力。 “我能奉献的没有其他，只有热血、辛劳、泪水与汗水”。鼓掌
者，传递爱与力量，而做到这些，除了付出等质的热血与辛劳，别无他法。 同为战争时期的又一强大的女性：南丁格尔就诠释了这种奉献。出身名门的她不图回报，在战后默默地用自己的力量支持着战士们，她照料垂死病人，终日奔忙，她在物质生活里的需求如此微少，她坚持等到最后一名战士离开，她才离开战场。她的精神已经超脱了自我，她的奉献与牺牲在精神世界里显得无比巨大，她用爱的掌声抚平了战士们的伤痛，伤病员写道“那些寒夜因为她而充满了温暖……” 人世间正是因为有了这样的鼓掌者，有这样将把自己的精神力量奉献给别人的人们啊，生活的希望才如此朝气蓬勃。“生命的用途其实不在长短，而在于人们怎么用它，许多人活的日子不多，却活了很久。”假如我有能力成为谁心中的精神支柱，我将努力的把这个神圣的任务做好。 是啊，我们在低潮的时候需要鼓励，需要正能力的支持，所以我们要友善的给四周的人一些正能力。 【篇二】 现代社会的节奏快速跳动着，许多人都忙繁忙碌地过完一天又一天3951为事业、学业和家庭而奋斗着，因此堆积的压力就越来越多3很少有人有乐观的生活态度积极安康的为人处事。因此，生活反而会成为一种承担!所以，生活需要“正能量”! 何谓“正能量”?这词原本是天文学的专有名词，后来英国的学
以正能量为话题的心得作文精选5篇 以正能量为话题的心得作文精选1 寻找微尘的踪迹，我们发现了这样一个新名词——正能量。它把微尘融入其中。起初微尘是青岛一位数次捐款不留姓名的普通市民;后来，逐渐扩展成一个关爱他人的爱心符号。再后来，以微尘命名的爱心群体，走进青岛的大街小巷。 20_在我们身边，红飘带、微尘等越来越多的人积极投入到传播“正能量”的洪流中。 盛夏的青岛，少了几丝清风拂面，多了几分蝉的嘈杂。我正准备和妈妈去补习班，车子走到中途，上来一位带着孩子的妇女。我看见前面的一个年轻的哥哥站起来给她们让座。过了两站，那位让座年轻人下去了，车子重新行驶起来。突然，车子突然猛烈地歪斜了一下，我本能的向前看去，本想知道发生了什么，却看到这样一副景象：在急刹车时，我前面的小孩重心不稳的向前面的栏杆撞去，还发出了呼救声，而他旁边的另一位年轻人则毫不犹豫的伸手挡在了栏杆上，让那个小孩撞在了他的手上，幸免了一场悲剧。
如果让我来评论，那他一定是“最美乘客”。在当今社会，有很多侠肝义胆的热心人，在他们身上蕴藏着的“正能量”，正在温暖我们这个社会，改善我们这个社会。 正能量是指引人们前进的灯塔、是鼓动人们前进的风帆和是团结各种力量共同奋斗的纽带。社会需要爱，时代呼唤爱。赠人玫瑰，手留余香。在当今社会，我们需要正能量。 生活中，“正能量”带来的正效应确实不少。正如我们在生活中，阿里木带给我们的感动，他靠卖烤肉资助贫寒学子，而不少人专程去“捧场”，这里面有感动，也有“正能量”的传递。还有黑龙江最美女教师张丽莉，为救学生被压断双腿。 其实，在我们有困难时、无助时、烦闷时，在我们渴望他人帮助时，我们也需要一个充满正能量的环境，这样，这些烦恼就可以化为乌有了。 现在，当美丽这一并不新颖的词汇与中国、青岛相连时，给人的感受是全新的，它不仅是一个形容词，更是一个动词! 以正能量为话题的心得作文精选2 记得有一次我们全家去植物园，在路上，看见一个树桩，我指着树桩横截面上一圈圈的痕迹，好奇的问妈妈，这是怎么出来的?妈妈听了，笑了一笑，指着树桩上的圈圈说：这是树的年轮，它显示了树的年龄。
平板台制动计算公式 一、前轴 1、前轴行车制动率=（最大行车制动力左+最大行车制动力右）÷【（动态轮荷左+动态轮荷右）×0.98】×100% 2、前轴不平衡率=（过程差值大-过程差值小）÷最大行车制动力中大的值×100% 二、后轴 1、后轴行车制动率=（最大行车制动力左+最大行车制动力右）÷【（动态轮荷左+动态轮荷右）×0.98】×100% 2、两种情况算法 （1）后轴行车制动率＞60%时 后轴不平衡率=（过程差值大-过程差值小）÷最大行车制动力中大的值×100% （2）后轴行车制动率＜60%时 后轴不平衡率=（过程差值大-过程差值小）÷【（动态）轮荷之和×0.98】×100% 滚筒制动台计算公式 一、前轴 1、前轴行车制动率=（最大行车制动力左+最大行车制动力右）÷【（轮荷左+轮荷右）×0.98】×100% 2、前轴不平衡率=（过程差值大-过程差值小）÷最大行车制动力中大的值×100% 二、后轴 1、后轴行车制动率=（最大行车制动力左+最大行车制动力右）÷【（轮荷左+轮荷右）×0.98】×100% 2、两种情况算法 （1）后轴行车制动率＞60%时
后轴不平衡率=（过程差值大-过程差值小）÷最大行车制动力中大的值×100% （2）后轴行车制动率＜60%时 后轴不平衡率=（过程差值大-过程差值小）÷【轮荷之和×0.98】×100% 注：（1）机动车纵向中心线位置以前的轴为前轴，其他轴为后轴； （2）挂车的所有车轴均按后轴计算； （3）用平板台测试并装轴制动力时，并装轴可视为一轴 整车制动率 整车制动率=最大行车制动力÷（整车轮荷×0.98）×100% 驻车制动率 驻车制动率=驻车制动力÷（整车轮荷×0.98）×100% 台式检验制动率要求（空载） 台式检验制动力要求（加载）
以传播正能量为话题的高中作文 经历这些时光的时候，并没有觉得青春有多么珍贵——每一段青春都应是发光体。但 在写这些文字的时候，却深深感受到“37.8℃的青春”才是青春所散发的热度。 “你觉得孤单就对了，那是让你认识自己的机会;你觉得不被理解就对了，那是让你 认清朋友的机会;你觉得黑暗就对了，那是让你发现光芒的机会;你觉得无助就对了，那样 你才能知道谁是你的贵人;你觉得迷茫就对了”——《谁的青春不迷茫》出自于刘同的文章。相信跟我一样看了这本书的人一样跟我感触很多吧。如果，你和我一样看到这篇文章 还是会有很多的思考，还是会回忆着自己曾经过往的成长与青春的话那么恭喜你同时也谢 谢你你的青春从现在开始起步并且你还没有放弃你自己。我们每个人都无关完美，只是， 我们现在能开始努力至极，将不完美变成完美，化缺点为优点，总结出一个你认为最完美 的自己，然后趁现在我们都还年轻再战一回。 “我的人生是一栋只能建造一次的楼房，我必须让它精确无比，不能有一厘米差池。 所以，我太紧张，害怕行差步错”——《致青春》出自于陈孝正的经典台词。这是当下最 流行的话题也是最流行的电影，看了这部电影我想多少都会勾起我们对青春的记忆。曾经 我们都义无反顾的为了追求一念天堂、一念地狱而抉择过。现在得到的却是对当年那一份 遗失的美好追悔莫及;在某种程度上我们也许是成功的，但是我们失去的也是心灵的救赎。年轻人有梦想就要勇于去追求，不管走多远都要记住不因生活的压力，琐事的烦杂，将我 们变得麻木，冷漠，行色匆匆中，其实青春就是努力，倔强，不服输。现实总是很残酷， 但是希望在未来的日子，我们不为了生活而忘了梦想，不为了老练而丢弃冲动，不为了成 熟而失去格调。记住虽然我们不能改变人生的长度，但是可以改变人生的厚度。 无论时代发展到何种地步，有三样东西永不褪色，那就是：感恩、信用、期盼。崇高 真挚的品德用眼睛看不到，却可以用心灵去感受，当我们受到恩惠时，只要怀着感恩的心，就可以走进一片更广阔的天地，在爱的词典，没有重量，负担，危险，有的只是奉献，无私，同样在感恩的词典里，也只有无限颗感恩的心。每个人都需要爱，因为有爱，生活才 充满希望：因为被爱，生命才能懂得付出和回报。感恩生活中的每一个人吧，因为感恩可 以收获善良与感恩。我们的青春因为有了感恩的色彩，所以五彩斑斓。 “你只闻到我的香水，却没有看到我的汗水;你有你的规则，我有我的选择;你否定我 的现在，我决定我的将来;你嘲笑我的一无所有，不配去爱，我可怜你总是在等待;你可以 轻视我们的年轻，我们证明这是谁的时代;梦想是注定孤独的旅行，路上少不了质疑和嘲笑，但那又怎样，哪怕遍体鳞伤，也要活的漂亮”——《聚美优品》创始人陈欧我为自己 代言。伸出双手就能拥抱全世界。世界其实不大，只要你愿意踏出第一步，世界就在你脚下。当你站在那个夏天的海岸线，其实我都知道我们还是心里面那个狂热的少年。 我不想错过青春，更不想虚度青春。再不疯狂我们就老了。亲爱的我们青春没有彩排，我们的青春正在进行时。现在开始问自己一个问题：“准备好了吗”?
鼓式制动器制动力矩的计算 1、制动器效能因数计算 根据制动器结构参数可知： A 、 B 、 C 、r 、φ、（结构参数意义见附图二） 其中θ为最大压力线和水平线的夹角。 由以下公式计算μ＝0.35时（μ为摩擦片与制动鼓间摩擦系数），制动器领蹄和从蹄的制动效能因数。 θ=)tan(B C ar μγt a n ar = )t a n s i n s i n t a n (θφφφφθ+-=ar e θθγλ-+=e θθγλ+-=e ' φφφρsin 2sin 4+= r B A +=ξ r C B k 22+= 领蹄制动效能因数: 1sin cos cos 1-=?γ θρλξ?e k K
从蹄制动效能因数: 1 sin cos 'cos 2+=?γθρλξ ?e k K 制动器的总效能因数，可由领、从蹄的效能因数按如下公式计算： 2 11 24??φ?????+?=K K K K K 2、制动器制动力矩计算 单个制动器的制动力矩M 为： R P K M ??= 其中：K 为制动器效能因数 P 为制动器输入力，加于两制动蹄的张开力的平均值； R 制动鼓的作用半径,即制动器的工作半径r 制动器输入力η??=i F P /2 其中：F 为气室推杆推力，由配置的气室确定 i 为凸轮传动比，e L i /= （L 为调整臂臂长，e 为凸轮力臂，即凸轮基圆半径） η为传动效率，一般区0.63 例：某Φ400X180制动器，A=150 B=150 C=30 r=0.2 Φ=115° μ＝0.35 η＝0.63 通过上公式计算得1??K ＝1.530 2??K =0.543 2 11 24??φ?????+?K K K K K ＝＝1.603 取F=9900N(0.6MPa 气压下气室输出力) L=125 e=12 R P K M ??=＝R L F K ????η/2e=1.603*9900*125*0.63*0.2/(2*12)
《机动车运行安全技术条件》（GB7258-2004）有关制动方面的： 1.1 台试检验制动性能 1.1.1 行车制动性能检验 1.1.1.1 汽车、汽车列车在制动检验台上测出的制动力应符合表 6 的要求。对空载检验制 动力有质疑时，可用表 6 规定的满载检验制动力要求进行检验。 摩托车及轻便摩托车的前、后轴制动力应符合表 6 的要求，测试时只允许乘坐一名驾 驶员。 检验时制动踏板力或制动气压按7.13.1.3 的规定。 表 6 台试检验制动力要求 1.1.1.2 制动力平衡要求（两轮、边三轮摩托车和轻便摩托车除外） 在制动力增长全过程中同时测得的左右轮制动力差的最大值，与全过程中测得的该轴左 右轮最大制动力中大者之比，对前轴不应大于20% ，对后轴（及其它轴）在轴制动力不小 于该轴轴荷的60% 时不应大于24%；当后轴（及其它轴）制动力小于该轴轴荷的60% 时，在制动力增长全过程中同时测得的左右轮制动力差的最大值不应大于该轴轴荷的8% 。 依据国标要求，对前轴以外的制动力平衡计算分两种情况： 1、当该轴制动制动率 >= 60%时，过程差最大差值点的两个力分别 为f1和f2，如果f1 >= f2 不平衡率 = （f1 –f2）/f1 * 100 ； 如果f1 < f2不平衡率 = （f2 –f1）/f2 * 100 2、当该轴制动制动率 < 60%时，过程差最大差值点的两个力分别
为f1和f2，如果f1 >= f2 不平衡率 = （f1 –f2）/轴重 * 100 ；如果f1 < f2不平衡率 = （f2 –f1）/轴重 * 100 注意：以上为简约的计算，较为准确的计算要注意单位之间的换算：轴重是kg，制动力的单位是10N 例如： 轴重最大左最大右差值左差值右制动率不平衡率 2074 543 508 543 508 50.7 1.7 二轴不平衡率（ 543-508）*10/(2074*9.8)*100= 1.722% 有关制动台仪表 制动台仪表的不平衡率算法说明书没有给出，不清楚其算法，对于前轴有可能是对的，对于后轴等仪表算法可定是错误的，制动台本身不能得到车辆的轴重，也就不能判断制动率是否 >=60，也就不能得出不平衡率。
传播正能量 生活需要正能量，社会需要正能量世界更需要正能量。 但是如今，小悦悦事件彭宇案这一幕幕令人惊心的画面又该怎样解释？难道这就是所谓的正能量吗？不是的，这只是一小部分的不足与缺失，要相信，这个社会上还是充满正能量的！有这样一件事，有一天一个男孩去上学，但由于不小心把一辆私家车给划了，一般的孩子肯定是先溜了再说别的，但是这个小男孩并没有这样做，反而，他一直在等车主，终于等不上了他还不忘写一张字条留给车主向车主解释。 车主看到后深受感动，它不仅没有向孩子索要赔偿，并且还免了男孩应付的一切费用。 男孩的举动不就是正能量的真实体现吗？男孩的行为像一股清泉，灌溉着我心田的每一个角落。 汶川大地震，众所周知，伤亡惨重，但是又有多少的抗震救灾战士和志愿者从这伤亡惨重中挽回了多少条百贵的生命，甚至有些志愿者和抗震救灾战士为了挽救别人不畏牺牲自己，这种品质是高尚的！是值得流芳千古的！但是你想错了，他们这样做不求名也不为利，他们只是平平淡淡的做自己该做的事，在自己的工作岗位上默默无闻的奉献着，也许作为后人的我们没人会记得他们，但历史不会遗忘那些抗震救灾战士和志愿者无疑是最值得我们歌颂的！再谈谈古人，他们的生活比现在艰苦的多，那是什么都没有全凭一颗大脑。
蒲松龄，历史巨著《聊斋志异》的作者，创作时条件异常艰苦，但这并没有成为他向命运屈服的理由，反而他更坚强，意志更坚定，凭借一个小茶馆用一杯杯茶水换取路人的一个个神奇故事，终于克服种种困难完成了这本巨著，蒲松龄这种坚持不懈不向命运低头，不屈服于条件的精神品质感动了无数后人。 从古至今，有许多古人和后者都在默默的传递正能量，而我，只想做这大链条上的一份子，在生活中，在社会上把这份正能量，这份温暖这份爱悄无声息的接力下去，我很期待一个充满正能量的世界，让我们都行动起来，唤醒每个人内心深处的良知，一起携手，把正能量传递下去！
制动扭矩： 领蹄： 111????=K r F M δ 从蹄：222????=K r F M α 求出1??K 、2??K 、1F 、 β θ 2F 就可以根据μ计算出制 动器的制动扭矩。 一．制动器制动效能系数1??K 、2??K 的计算 1．制动器蹄片主要参数： 长度尺寸：A 、B 、C 、D 、r （制动鼓内径）、b （蹄片宽）如图1所示； 角度尺寸： β 、 e （蹄片包角）、α（蹄片轴中心---毂中心连线的垂线和包角 平分线的夹角，即最大单位压力线包角平分线的夹角，随磨擦片磨损而增大）； μ为蹄片与制动鼓间磨擦系数。 2．求制动效能系数的几个要点 1）制动时磨擦片与制动鼓全面接触，单位压力的大小呈正弦曲线分布，如图2，max P 位于蹄片轴中心---毂中心连线的垂线方向，其它各点的单位压力 σsin max ?=P P ； 2）通过微积分计算，将制动鼓 与磨擦片之间的单位压 力换算成一个等效压力， 求出等效压力的方向σ 和力的作用点1Z 、2Z （1OZ 、2OZ ），等效力 P 所产生的摩擦力1XOZ （等于μ?P ）即扭矩(需建 立M 和蹄片平台受力F 之间的关系)；实际计算必须找出M 与F 之间的关系式： ????=K r F M
3)制动扭矩计算 蹄片受力如图3： a. 三力平衡 领蹄：111OE H M ?= 从蹄：222OE H M ?= b. 通过对蹄片受力平衡分析（对L 点取力矩） ()1111G L H b a F ?=+? ()1111/G L b a F H +?= ∴ ()11111/G L OE b a F M ?+?= 111????=K r F M ∴ 111 1G L OE r B A K ? += ?? 同理： 2 22 2G L OE r B A K ? += ?? c. 通过图解分析求出1OE 、2OE 、11G L 、22G L 与制动器参数之间的关系，就可以计算出1??K 、1??K 。 3．具体计算方法： 11-?= ?ρ γ?K l K ； 1'2+?= ?ρ γ?K l K r B A l +=； r C B K 2 2+= 1) 在包角平分线上作辅助圆，求Z. 圆心通过O 点，直径＝e e e r sin 2sin 4+?
传播正能量文章 有时候，我们就是需要一些正能量的文章来充实自己，来让自己也学会做一个励志的人。下面是为大家整理的关于传播正能量文章的相关资料，供您参考! 传播正能量文章篇1：我们还能混多久 混，也可谓一种生活，但真正的生活是混不了一辈子的。现在开始混日子，老来之时，遍是无日子可混，无生活可享，从而后悔莫及，遗憾终生。 越来越习惯安逸，越来越害怕冒险，越来越逃避责任，越来越淡化理想，开始所谓的平静生活，平淡心态，而事实却只是自欺欺人。当一天和尚撞一天钟，日复一日，年复一年，看似无欲无求，实则内心彷徨;看似随遇而安，实则斗志丧失;看似平静淡雅，实则危机四伏。自古有云，居安思危，而现在已慢慢忘却了梦想，渐渐融入了安逸，对于安逸之中隐藏的危机，视而不见，直至危机四伏，才措手不及，深感后悔，却是悔之晚矣。时常反思现在的自己，偶尔遐想未来的自己，细细品味却发现，那只是一个空洞的梦想，可望而不可及，可求而不可遇，若以目前的状态继续前行，无论何时都不可能达到自己预期的目标，看看现在，想想未来，就会控制不住的心慌，情不自禁的烦躁，在理想与现实中矛盾着，在感性与理性中纠结着，在忘我与自我中无奈着，想要改过自新，却是无从下手;想要痛改前非，却是无
力回天。 现在的自己如同温水中的青蛙，在慢慢等待着死亡来临的那一刻，每天过着同样的日子，虽有小波澜，却难以引起足够斗志;每天都会无所事事，虽偶有忙碌，却只是闲多忙少;上班时盼望着下班，下班后期盼着自己的小天地，将烦恼抛却，将思绪放纵，一天中最幸福的时刻或许只有睡觉，忘却了现实，超脱了自我，偶尔做个美梦，将灵魂尽情翱翔于梦境深渊。而自己很清楚，这只是在逃避，逃避现实，躲避责任，长此以久，必然是碌碌无为，庸碌一生，想要终结，却是举目无措，明知是错，却不思悔改，明知失败，却一意孤行，内心痛苦而无奈，却不知如何自救。 现实中或许有很多人同我一样，混沌的过着日子，得过且过，盲目的追随着目标，却看不到前方的路，混着日子，却做着白日梦，下着慷慨的承诺，过着我行我素的生活，表着激昂的决心，继续着唯我独尊的日子，不思悔改，不求上进，偶尔静心反思，才知自己已远离目标，寂夜反省，才觉自己已走入歧途。明明是亡羊补牢，为时不晚，却总是心有余而力不足。混沌的日子，究竟何时了结?庸碌的岁月，究竟何时终结? 古语有云：人贵有自知之明。而事实呢，我们往往自知而不自制，又有何用?平凡的人满地都是，而真正的人才却是屈指可数，在身体上人与人之间都是相差无几的，而欠缺的只有思维，人因为有了独立思考的能力，故而高级，故而神秘，也就是因为思维而将人类划分开来。每个人都或多或少的存有压力，而又有几人能将压力化作紧迫感，
传播正能量文章摘抄3篇 ----WORD文档，下载后可编辑修改---- 下面是小编收集整理的范本，欢迎您借鉴参考阅读和下载，侵删。您的努力学习是为了更美好的未来！ 传播正能量文章摘抄：天分是持续不断的忍耐剑桥何以能是剑桥?因为它能从生命的平凡中见出不平凡来，或者它能把生命的平凡硬是锻造成不平凡。剑桥的这些迷人的故事让我真正领悟了思想家伏尔泰的话：天分乃是持续不断的忍耐。 每次读金耀基先生的《剑桥语丝》，我总要细细品味那篇“剑桥一书贾”，让心灵一次又一次重温他笔下饱含真情流淌出的那些“充满人间温暖与尊严的故事”。我虽尚无缘份走进梦中的剑桥，金先生的文字却让我开始思索剑桥何以能是剑桥。 金先生说，剑桥人对所有地位显赫的“剑桥之子”固然会用各种方式表达出感念和爱戴，就是对在世俗眼中普通得不能再普通、却对剑桥做出过贡献的人也同样肃然起敬： 一位负责大学打字室工作的少女，在这样平凡的岗位上一干就是五十多年，兢兢业业，任劳任怨，把美丽和青春化作打字机上的一个个单调的字符，敲出了生命的星光，成为剑桥有史以来第一位获得荣誉博士学位的女性; 一位石匠，默默无闻，一斧一斧地凿击，把一生的心血融化进剑桥宏伟建筑的石块中，让生命的坚毅变成永恒，剑桥人感念他，授予了他同样高的荣誉;
一位旧书商在剑桥经营书店，为剑桥学子提供了无数精神食粮，四十年风雨无阻直到生命的时钟走到了最后一刻。剑桥人感念他，破例以剑桥大学出版社的名义为他出了纪念文集。 传播正能量文章摘抄：活着的最高境界其实和你一样----他出身卑微，却身怀远大理想。多年前，他在1983年版的《射雕英雄传》中扮演那个宋兵乙，为增添一点点戏份，他请求导演安排“梅超风”用两掌打死他，结果被告之“只能被一掌打死”。这个年轻时被称作“死跑龙套的”卑微小人物，第一次当着导演的面谈到演技时，在场的人无一例外都哄堂大笑。但他依然不断思索、不断向导演“进谏”，直至2002年自己当上导演。那年，他获得了金像奖“最佳导演奖”。 其实和你一样----上世纪90年代，在一趟开往西部的火车上，梳着分头、戴着近视眼镜的他看上去朝气蓬勃，内心却带有微微的彷徨。那时的他严肃乏味，常常独坐好几个小时不说话。后来转行做主持人，1998年他第一次主持的电视节目播出时，他发现自己说的话几乎全被导演剪掉了。他让身为制片人的妻子准备了一个笔记本，把自己在主持中存在的问题一一记录下来，哪怕是最细微的毛病都不肯放过，然后逐条探讨、改正。即使今天其身价已过4亿，成为中国最具影响力的主持人，他仍未放弃面“本”思过。 其实和你一样----10年前，他是大学里的“小混混”，由于经常逃课而被老师责备。毕业后被分到当地的电信局当小职员，面对冗杂的机关工作，他感到既劳累又苦恼，后来他勇敢而果断地辞了职，
制动计算 制动系统方面的书籍很多，但如果您由于某事需要找到一个特定的公式，你可能很难找到。本文面将他们聚在一起并作一些的解释。他们适用于为任何两轴的车辆，但你的责任就是验证它们。并带着风险使用..... 车辆动力学 静态车桥负载分配 相对重心高度 动态车桥负载（两轴车辆） 车辆停止 制动力 车轮抱死 制动力矩 制动基本原理 制动盘的有效半径 夹紧力 制动系数 制动产生 系统压力 伺服助力 踏板力 实际的减速度和停止距离 制动热 制动耗能 动能 转动能量 势能 制动功率 干式制动盘温升 单一停止式温升 逐渐停止式温升 斜面驻车 车桥负荷 牵引力 电缆操纵制动的损失 液压制动器 制动液量要求 制动基本要求 制动片压缩性 胶管膨胀 钢管膨胀 主缸损失 制动液压缩性 测功机惯性
车辆动力学 静态车桥负载分配 这里：Mf=静态后车桥负载（kg）；M=车辆总质量（kg）；Ψ=静态车桥负载分配系数注：对于满载和空载的车辆的变化往往是不同的。 相对重心高度 这里： h=重心到地面的垂直距离（m）；wb=轴距；X=相对重心高度; 动态车桥负载（仅适用于两轴车辆） 制动过程中车桥负载的变化与哪个车桥制动无关。它们只依赖于静态负载条件和减速度大小。 这里：a=减速度（g）；M=车辆总质量（kg）；Mfdyn=前桥动态负载（kg）； 注：前桥负荷不能大于车辆总质量。后桥负荷是车辆质量和前桥负荷之间的差值，并不能为负数。它可能脱离地面。（摩托车要注意）！ 车辆停止 制动力 总制动力可以简单地用牛顿第二定律计算。 这里：BF=总制动力（N）；M=车辆总质量（kg）；a=减速度（g）；g=重力加速度（s/m2）；车轮抱死 如果车轮不抱死只能产生制动力，因为轮子滑动摩擦力比滚动摩擦力低得多。在车轮抱死前特定车轴可能的最大制动力计算公式如下： 这里：FA=车桥可能的总制动力（N）；Mwdyn=动态车桥质量（kg）；g=重力加速度（s/m2）；μf=轮胎与地面间摩擦系数； 制动力矩 决定了哪个车轮需要制动来产生足够的制动力，每个车轮扭矩的要求需要确定。对于某些规则，前部和后部制动器之间的分配是确定的。这可能是通过不同的刹车片大小或更容易使
篇一：传递正能量作文 正能量其实是一种积极向上，乐观阳光的态度，它就好比是一杯酒，喝一口，令人陶醉，浓浓的醇香，令人回味——题记 现在报纸、电视上总会报导一些新闻XX因被撞之后未能及时抢救，失血过多而死XX因扶摔倒老人，而被冤枉。一条条悚目惊心的新闻，一张张惨不忍睹的图片，犹如鞭子，一下一下地抽打着我们的心。小悦悦案让我们看到人性的冷漠，彭宇案让我们看到世态的炎凉。道德之火在一点一点熄灭，只剩下了微弱的火光。我们的社会多么需要伸张正义的人，我们多么希望惨案少些，再少些。 终于，我看到了曙光：一些向人们传递着正能量的高尚的人。 龚金川，是一所小学的校长，十四岁痛失了一条右臂，但他身残志坚。一天早上，他正在江边晨练，忽听扑通一声，一个重物砸进江中。紧接着，他又听到了惊慌失措的呼救声，看到了江面上漂浮着几缕银丝。他仿佛意识到了什么，奋不顾身地纵身一跃，跳入江中。风呼呼地吹着，寒冬的残阳无力地照射在江面上，刺骨冰冷的江水向他袭来，可这并不能动摇他救人的决心。他用右肩顶起了老人，左手不停地划水。江水不断地向他涌来，犹如黄金巨蟒般缠着他。这对于身高仅165米的人来说，是一种极限一种挑战，可他全然不顾，套住好心人丢来的绳子，一直坚持到了江边，成功救起落水者。回到家，家人看到他那水淋淋的样子大吃一惊，而他则是轻描淡写第说了句：掉水里了。他的事迹打动了无数的人，一股正能量犹如一泓清泉，流进了每个人的心田。 忘不了那一天，泉州市宏福园内哀乐低沉，泉州市领导和许多素不相识的市民，纷纷赶来为一位逝者送行。他不是什么领导，更不是什么伟人，但他，却是市民公认的最美公交司机。因为，在他生命结束的那一霎那，他用尽全力踩住刹车，保了一车人的性命。尽管他英年早逝，但他的精神犹如一股正能量，春风般，吹拂每个人的心灵。 因为大人们以身作则，就连孩子也成为正能量链条上的一份子。江苏一小男孩上学时不小心刮伤了一辆私家车，由于等不到车主，他留下了一张字条。车主知道后，深受感动，不仅没要求他加倍赔偿，还免了他的所有赔偿。男孩所传递的正能量，拨动着我们内心深处的那根弦。 正因为许多人都加入了传递正能量的行列中，因此，快熄灭的道德之火，终于又熊熊燃烧/zl/转载请保留 篇二：正能量，人之所需 纵观古今，多少人物尽付历史洪流，枯骨遗野名不经传者不胜枚举，唯有身怀正能量者方能名留千古，世人谓之风流人物。人需要正能量，由此方能修身齐家治天下，才能有所建树，不致荒废一生。 正能量是人身居困境不灭的理想。郭沫若评价蒲松龄为写鬼写妖高人一等，刺贪刺虐入
正能量的作文坚持正能量 导读：关于正能量的作文，坚持正能量 我们喜欢喝身上带有正能量的一起，因为和这样的人交往能将正能量传递给你，令你感染到那种积极快乐的感觉。而另一些人则相反，因为他身上负能量过多，不断地向你传递消极悲观的情绪。 蔡永康在接受记者采访时，对小S进行评价时说：“小S是个很好玩的人，她个性本身就是很乐天，很有活力，这个朋友让我觉得活着是一件很值得、很舒服、很有趣的事。有的人会让我觉得活着很没劲，碰到他会把我的能量都吸走。” 确实如此，和正能量多的人打交道时，你能感觉到：你跟他在一起感觉是安全的、放松的、亲近的，你觉得他浑身散发着诸如同情心、同理心或愿意去支持你的感觉。且有他在旁边，你会觉得比自己独处的状态更好，因为你的正能量也会跟着上升。 而和负能量多的人打交道，你却感觉到：你跟他在一起感觉不安全、紧张，处于防卫状态。你觉得是被吸取、削弱的感觉，你自己的正能量减少，负能量增加，感觉不舒服，自己是被挑剔的、挑战的和攻击的，你会很想逃走。 因为，他们把“负能量”，传递给了你，而本身“正能量“并不强大的你无法抗拒，接收了对方传递的负能量，连带传染到你自己也感觉诸事不顺。 所以做一个正能量的人非常重要，能够得到众人的认同和支持。
而如果周围人都认为你是一个负能量的人，对你的工作和人际关系都是破坏性的。 我们每个人身上都有正、负两种能量。我们需要做到的'是，找回自己的正能量，接纳、运用和传播更多的正能量，当负能量找上门来的时候，我们要学会拒绝接受或者积极转化。 畅销书作家大卫·波莱讲过一个例子： 我跳进一辆出租车，想去纽约中央车站。开始，一切都好好的，车子安全正常地行驶在右侧车道，突然，一辆黑色轿车冷不丁从旁边停车场冲山来，横在我们正前方，出租车司机猛踩刹车，车子侧滑出去，轮胎与地面发出尖锐的摩擦声，好不容易才停下来。当我反应过来时，出租车与黑色轿车后备箱仅一寸之隔，好悬。 “我惊呆了。但是，更令人吃惊的是，明明是黑色轿车的司机差一点酿成重大车祸，可他却探出脑袋，朝着我们破口大骂。甚至竖起中指，向我们示威! 随之发生的事情则更让我震惊不已，出租车司机竟然微微一笑，朝那个家伙挥挥手。我吃惊的是，他太友善了吧，于是，忍不住问他：“为什么你那么做呢，那个男人疯了，像要杀人一样!” 出租车司机回答到：“许多人就像垃圾车，他们装满了垃圾四处奔走。充满懊恼、愤怒、失望的情绪，随着垃圾越堆越高，他们就需要找地儿倾倒，释放出来。如果你给他们机会，他们就会把垃极一股脑儿倾倒在你身上。所以，有人想要这么做的时候，千万不要收下，
列车制动力计算 1，紧急制动计算 ??K(B?kN)?列车总制动力hh?K------全列车换算闸瓦压力的总和， ??K1000B?1000hh?(N/kNb?)列车单位kN；式中h?---换算摩擦系数；h 制动力的计算公式? (P?G)?g(P?G)?g?K???b?1000h?)kN(N?/其中，则hh h gG)??(P P?G------------列车的质量，式中 t； ?---换算摩擦系数；h?------------------列车制动率；h?K------全列车 换算闸瓦压力的总和，kN ；h b?c?1?，列车常用制动计算2 ????(N/?bb?1000kN)?由此可得chhcc?-----式中常c b 用制动系数c b-------列车单位制动力c p为列车管空气压力常用制动系数表1 1
3,多种摩擦材料共存时列车制动力的计算他们同一列车中的机车，车辆可能采用不同材料的闸瓦或闸片， 具有不同的换算摩擦系数列车总制动力应当是各种闸瓦的换算闸瓦压力与该种闸瓦的换算摩擦系数乘积的总和。即?????????）kN????K?KK?（）（K??B h3h1hh13hh2hh2代表车辆的闸瓦,式中，,代表机车的闸瓦制动，??KK2h1h2h1h代表车辆的盘形制动，等等。 制动，,?K3h3h???)(1000K?hh??)kN(1000b?(N?/)?列车单位制动力。hh g?(PG)? ，列车制动的二次换算法4 2 不同摩擦材料换算闸瓦压力的二次换算系数表 3 机车的计算质量及每台换算闸瓦压力表表
（）内是折换成铸铁闸瓦的换算压括号外是原闸瓦的换算压力值；注：换算闸瓦压力栏中，内是折算成新高摩合成闸瓦的换算压力值；《》力值；<>内是折算成合成闸瓦的换算压力值；内是折算成高摩合成闸瓦的换算压力值。[] 车辆换算闸瓦压力表表4
关于传播正能量的作文 导语：“正能量”指的是一种健康乐观、积极向上的动力和情感，是社会生活中积极向上的行为。下面是收集的关于传播正能量的，欢迎参考！ 正能量是一洌清泉，洗涤着人们的心灵；正能量是一股力量，冲击着人们的灵魂。或许这个世界没有我们想象中的美好，我们还笼罩在“小悦悦”等诸多人心冷漠的事件中。但是，我们身边一人存在着许多正能量，他们用生命谱写正气之歌，以实际行动传播着正能量。 xx年7月，我省遭受了今年9月超级台风“威马逊”侵袭。全省普降暴雨，特大暴雨，给人们群众的财产和生命安全带来了严重的威胁，然而，风雨无情人有情。众多人民群众挺身而出。他们临危不惧，挺身而出，他们是人们的英雄，他们在风雨中永生。 邓育军生前是清运小区的一名驾驶员，在灾后卫生清理工作中，他主动加入垃圾清运突击队，为争分夺秒将路面清理干净，邓育军在工作岗位上连续作业六天六夜，在某日中午作业过程中，车辆发生意外后仰倾覆，邓育军因公殉职，年仅33岁。平凡的岗位折射出伟大的人格，他是人民的英雄，他舍小家而为大家的精神值得我们敬佩，他用有限的生命为人们书写伟大二字。他是黑夜中的一束光，他是风雨中的顶梁柱，他是我们身边的正能量。 在“威马逊”特大台风中，一个又一个人民英雄涌现在我们眼前，他们的名字是那么响亮，又是那么令人心碎，因为每个名字所对应的，都是一个伟大的生命，都是一个救人的英雄。
超强台风“威马逊”重创海南电力系统后，温和同志连续六天 指挥抢修受损的电力设施，参与恢复灾区电力供应工作。xx年7月 23日，因过度劳累，突发心脏病，牺牲在抢救岗位上，终年46岁。温和叔叔虽然已经离我们远去，但是他的精神永远存在于我们的心中。他用46岁的生命点亮了万家灯火，也点亮了我们心中的灯火。鲁迅 曾说过，有的人活着，他已经死了；有的人死了，他还活着。温和叔叔已另一种方式活在我们心中，已无私奉献的精神鼓舞这我们重建家园。我们也将以各自的方式告慰英雄的离去；我们一定会用坚强的精神重建家园；我们一定会传承与发扬英雄的伟大精神。 信心感受一番才发现，原来正能量已经将我们包围，它就在我 们身边，如同空气般，我们无时无刻都需要它。在我们需要的时候，属于我们自己的正能量是指引我迈向成功的初始动力，身边的正能量鼓舞着我展望未来的美好。正能量如同春天的花香，夏天的微风，秋天的硕果，冬天的阳光。正能量无处不在，它需要我们去传播。 正能量可以将爱传递到每一个空间，可以照亮每一个黑暗的角落，可以沟通每一个友善的心灵。如今的中国正处于飞速发展的时代，科技发展，机械轰鸣。人心却被关闭在厚厚的 __中，人心越来越冷漠。这个时候，正能量的传递就如同明媚的阳光，消融了人与人之间的隔阂。 寻找正能量，传递正能量。正能量像滚雪球一样越滚越大。越 来越多的人参与其中。正能量已经逐渐变成一个个爱心的符号。
弘扬真善美传递正能量 李思佳 上个星期周五下午，我一到校就看见许多同学簇拥在宣传栏前观看，一边看还一边不停地发出啧啧的赞叹声，我连忙凑上前，原来是一封“表扬信”，这又是表扬谁呢？只见一张鲜红的纸上写着金灿灿的文字：三年级2班学生陈浩宇在周二下午课间活动时，拾到88元钱，在原地等候施主多时，未见有人来领，于是，把钱交给门岗值班老师，陈浩宇同学拾金不昧的精神值得大家学习…… 由此，我想，这真是一位可爱的同学，要知道，这88元钱对富家孩子来说可能算不得什么，但对于一般家庭的孩子这可能就是不小的数目了，这或许是他一周的生活费用，如果丢失了，他可能会遭到家长的责备、可能会忍饥挨饿，但是陈浩宇同学却没有见钱眼开，而是毫不犹豫地交给失主，他这种拾金不昧的精神能不值得大家敬佩吗？鸟美在羽翼，人美在心灵，人并不是因为美丽才可爱，而是因为可爱才美丽。 近年来，我校开展了“社会主义核心价值观“教育，引导青少年学生求真、向善、尚美，好人好事如雨后春笋一般层出不穷。如，帮同学修理凳子、补习功课、在学校里互相帮扶、嘘寒问暖……真是好人好事层出不穷。古人云“人之初，性本善”。可是，一说到真善美这三个字，人们似乎都以为这是伟人、圣贤者才可做到的事，离我们很遥远，可其实，人们只要用心观察，就会发现身边的真善美处处可
见。 上学期，我校举行田径运动会，最精彩的就是200米赛跑了。你瞧，200米起跑线上，运动员们个个精神抖擞，整装待发。只听到裁判员枪声一响，他们像离弦的箭向前冲去，场外的啦啦队员们不断地为他们加油鼓劲。看，跑在最前面的是四（1）班的小华，他昂着自信的头，不断向前冲去。紧跟在小华后面的是五（2）班的小青，他微微张着嘴，像踩着风火轮一样向小华逼近。经过顽强拼搏，小青终于超越了小华，场外响起了一阵阵欢呼声——离终点还有5米了。同学们仿佛看到了比赛的胜负。就在这千钧一发的时刻，小青脚下一滑，摔了个四脚朝天。 同学们都吓出了一身冷汗，我捂上眼睛都不敢看了。谁料，场外爆发起一阵阵热烈的掌声------我连忙张大眼睛一看，原来稳夺第一的小华停下了脚步，连忙扶起小青，关切地问：“小青，你伤得怎么样？痛不痛？“小青坚强地摇摇头。小华拉起小青，毫不犹豫地跑向终点，最后，他俩夺得了并列第三名，但他们获得的掌声和欢呼声是全场最多的。老师摸摸小华和小青的头，竖起了大拇指……在这次运动会中，拼搏奋进最美，赛出水平最美，但我认为友谊第一，比赛第二的小华是最美的。在表彰获奖同学时，老师要求同学们把赛场上的团结互助，永不放弃的精神带到学习生活中，做一个弘扬真善美，传递正能量的好学生。 这两件小事告诉我：真善美，是亘古不变的人之血脉；真善美，真切的存在于生活的每一天；真善美，汇聚无穷的力量。在这个生机
身边人传递正能量的故事作文 传递正能量的故事作文。让我们相信人性的正能量。下面是给大家整理的身边人传递正能量的故事作文，供大家参阅! 身边人传递正能量的故事作文：偶像正能量偶像，这是一个具有多重意义的名词。通常，我们把它理解为受人崇拜或尊敬的一类人。在我眼里，我的偶像一定是一个能带给我向上精神的人。而这样的一个人，就叫做阿尔伯特;爱因斯坦。 爱因斯坦是一个美籍德裔犹太人，同时他也是一名伟大的人物：他被公认为是继牛顿，伽利略之后最伟大的科学家，物理学家。他创立的“相对论”为核能开发奠定了基础，有着极其重要的价值。而正是这样一个了不起的人物，他的才智却并非早就显现出来的。 在刚开始上学时，爱因斯坦被老师看做是一个“不爱言语的小老头”。他极少和同学们交往，似乎还有些自闭。就这样，爱因斯坦默默地度过了几年。直到某一天，他转学去了另一所学校。那里健全的设备和热情的老师给了他极大的鼓励。从此他开始沉浸在科学的世界里。并且研究出了一系列成果。 小时候的我，总是认为，这个世界是没有秘密的，它把一切都敞开在人类面前，毫无神秘感。但逐渐长大以后，我才发现，原来这个世界有这么富哦令人匪夷所思的事情。尤其在了解了爱因斯坦这个人物后，我便开始寻找身边那些奇怪的现象，并试图用科学去解释它。
因为有爱因斯坦这个偶像，我明白了探求才能造就真理;因为有爱因斯坦这个偶像，我知道了信念支持人生;因为有爱因斯坦这个偶像，我懂得了别人的眼光并不重要。哪怕这一秒你并不被认可，但只有你努力，总有一天能让整个世界瞩目你的成就。 爱因斯坦说：“The value of a man should be seen in what he gives and not in what he is able to receive。”我认为他做到了，而我也向着这个目标努力奋斗着。虽然爱因斯坦已经逝世多年，但只要我们心怀对科学的热爱，他的精神就永远不会消失。我的偶像爱因斯坦带给了我前进的正能量，因此我崇敬他! 身边人传递正能量的故事作文：让我们相信人性的正能量必须承认，这个世界并不总是那么的美好，我们的人性也并不总是那么的高尚。“小悦悦事件”、“彭宇案”都曾经一度让人们感到道德的迷茫：为什么好人得不到好报，为什么周围都是冷漠的目光?于是，有人沮丧，有人彷徨，似乎人们已经找不到方向，似乎社会已经失去了力量。 但张丽莉、王世伟等六位龙江英雄的事迹一次次告诉我们：世界的真相，并不是这样!社会也好，人性也罢，都有着像硬币一样的正反面，我们不要以为看到了一面就看到了答案，这个世界，有黑暗就有光亮，有失望也有希望。而这光亮与希望，其实，就在我们每个人身上。 我们在报道中看到，当护士拉开窗帘，张丽莉看见照进病房的阳光，不禁由衷地感叹：“活着真好。”而在张丽莉、王世伟、荆百岁、谢尚威、高铁成、郭肖岐等人的身上，也让我们看到了同样的阳光，
传递正能量作文600字 作者:1303班廖米娜 那是考试的第二天，也许是因为天气太冷，闹钟已经响了好久我仍不想起床。多睡了十几分钟，匆忙的吃了几口早餐就走。从家里下来时天下起了小雨，望着阴沉的天空我迅速戴起帽子，跑向出租车，不小心踩了一滩水，溅的满裤子都是。 搭上出租车，报上学校的名字，终于松了一口气。 窗户白蒙蒙的，看不见车窗外的景色，朦朦胧胧像极了司机没有交点的双眸。直到下车时的开门声才打破了这车中的宁静，一打开车门冰冷的风像疯了似的一拥而入，把我瞬间吹醒，雨下得更大了。看着对面闪烁的绿灯变成红色，无奈只能独自站在一旁等待，雨点打在我的帽子上、衣服上、书包上，像一颗颗子弹，发出砰砰的声音，心情就像这阴沉的天气。我把冰冷的手放在口袋里，看着人们哈出的白气。 突然感觉旁边有一股温暖平稳的气息，我往左边一看是一个和我一样穿着校服的女孩，她手中举着伞对着我微笑，雨点从伞上划过地在我的脚边。红灯变成绿灯，我轻盈的走过斑马线。虽然不知道那个小女孩的名字，但当他把伞举在我的上边，我感觉一股暖流从心中流过。也许下一次我也会在另一个虚不相识的人上边撑起这把伞，这大概就是传递正能量吧！他那扑闪扑闪的大眼睛在我的脑海中回事不去。 我们应该传递正能量，可以是一声礼貌的的问候、一个温暖的微笑或是一次热情周到的服务，都有可能给予别人强大的力量。也是有大家都投入传递正能量的队伍中，有一分热发一分光，才能让我们的班级更好，让我们的学校更好，让我们的社会更加和谐，让中国更加美丽。 从现在开始，从身边的小事做起，让我们一起来做正能量的传递者。 2 用脚步也能丈量人生作文800字 用脚步也能丈量人生作文800字