Has a private sector emerged in China's industry Evidence from a quarter of a million Chinese firms

Has a private sector emerged in China's industry?Evidence from a quarter of a million Chinese firms

Sean DOUGHERTY a,?,Richard HERD a,?,Ping HE b

a

OECD Economics Department,2rue AndréPascal,75775Paris Cedex 16,France b

China National Bureau of Statistics,57Yuetan Nanjie,Beijing 100826,China

Abstract

This paper assesses the progress of China's transition towards a market economy by examining the structure of ownership,productivity,and profitability,as well as the concentration of production across firms,industries,and regions.It does this by analyzing a database of firm microdata of the quarter of a million industrial companies in operation during the 1998–2003period.Results show that the private sector now accounts for more than half of industrial output,compared with barely more than a quarter of it in 1998,and operates much more efficiently than the public sector.Higher productivity has fed through to improved profitability,motivating greater regional specialization of production.These changes are consistent with what would be expected in a market-based economy and suggest that reforms are making rapid progress.?2007Elsevier Inc.All rights reserved.

JEL classification:D4;F15;L11;O12;P23

“I watched a snail crawl along the edge of a straight razor …crawling and surviving ”—Francis Ford Coppola 1.Introduction

China's transition from a planned towards a market economy over the past 25years is in many ways remarkable.Highly unorthodox economic reforms were pursued in a decentralized manner,in keeping with political concerns,but often at the risk of creating new

self-propagating

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?Corresponding authors.Tel.:+33145248200;fax:+33144306165.

E-mail addresses:Sean.DOUGHERTY@https://www.sodocs.net/doc/085976319.html, (S.Dougherty),Richard.HERD@https://www.sodocs.net/doc/085976319.html, (R.Herd).1043-951X/$-see front matter ?2007Elsevier Inc.All rights reserved.doi:10.1016/j.chieco.2007.02.006

310S.Dougherty et al./China Economic Review18(2007)309–334

Table1

Share of transactions conducted at market prices

197819851991199519992003 Producer goods

Market prices01346788687.3 State guided0231864 2.7 State fixed1006436161010.0 Retail sales

Market prices33469899596.1 State guided0191021 1.3 State fixed97472194 2.6 Farm commodities

Market prices64058798396.5 State guided2232047 1.6 State fixed933722179 1.9 Percent of transaction volume.

Source:China National Development and Reform Commission,Price Yearbooks and Lardy(2002). distortions.Moreover,many reforms were piecemeal and tentative at first and only accelerated gradually.The uneven path of these reforms led to well-founded concerns that the progression to a market economy could be derailed.1

This paper analyzes a new set of data that covers the most recent5years of reforms through2003. The dataset covers just over a quarter of a million unique firms that report their principal financial and economic results to the government on an annual basis.As a result of firm exit and entry,the number of operating firms in any given year is considerably less,amounting to between160,000 and200,000firms.The information covers all industrial companies with annual sales of over 5million yuan,and so represents a detailed insight into the development of the Chinese economy.

Private ownership was not an early feature of the reform process.Instead,local government owned enterprises were the early driver of reforms in the industrial sector through the1980s and early1990s.These enterprises were marked by their ambiguous property rights which made up for a weak regulatory environment and offered investors some protection from expropriation.2Overt private ownership on a significant scale has only emerged in the past decade(OECD,2005).

In the absence of private ownership,downstream prices were liberalized(Table1),under a dual-track system which allowed production over a set quota to be sold at market prices.While strengthening incentives,this partial deregulation of downstream prices with upstream prices set at relatively low levels left open large rents.While this approach built support for reform,its partial nature propagated distortions,in an incomplete regulatory environment with few rules governing competition behavior.

Concern about these and related distortions gathered pitch as appraisals of the reforms of the late1980s and early1990s revealed disturbing trends in the structure of production,prices, productivity,and trade.In a highly influential study,Alwyn Young(2000)found that the shares of different industries across provinces were converging rather than diverging(through1997),as 1Murphy,Shleifer,and Vishny(1992)illustrate the risks of getting the reform sequencing wrong,such as by introducing privatization before adequately liberalizing prices,while Lau,Qian,and Roland(2001)show that the Chinese reforms followed an apparently incentive-compatible path that sustained reform momentum even while creating(and then destroying)rent-seeking opportunities along the way.And see Maddison(1998)for a long view.

2The mechanics of these unorthodox reforms are laid out by Li(1996)and Che and Qian(1998).Empirical support can be found in Dougherty and McGuckin(2002).

would be expected if comparative advantage were playing a strong role in determining the structure of production.Young also observed that prices for industrial and retail goods were diverging rather than converging and marginal productivity was not converging across sectors,as would be expected if market forces were at work.With respect to trade,Sandra Poncet (2003,2005)found that inter-provincial barriers were having a marginally increasing negative impact on regional trade flows in the 1992to 1997period,whether looked at in aggregate or at the industry level.3

Even if one accepts the implications of Young and Poncet's studies for the period through 1997,further analysis using a variety of methods suggests that they may have reversed as time has passed.In terms of output shares of detailed industries,Bai,Du,Tao,and Tong (2004)find that measures of regional specialization appear to have bottomed-out in the early 1990s and improved in the period through 1998.In terms of prices,Fan and Wei (2003)and Xu and V oon (2003)examine the stationarity and co-movement of up-and downstream prices and find relatively strong evidence of convergence (or domestic integration)through 2000.4And in terms of marginal productivities,Zhang and Tan (2004)obtain evidence that these may have converged in the period through 2001.While a new input –output table is not available yet to update Poncet's analysis,direct survey evidence by the Development Research Center (Li,Liu,&Chen,2004)suggests that inter-provincial barriers have dropped dramatically in recent years.

We proceed first by assessing the rise of the private sector,second by examining its produc-tivity relative to the publicly-controlled sector,third by decomposing the turn-around in prof-itability into subcomponents,and finally by measuring the extent of reallocation of production and consequential increase in specialization that the ownership transformation has stimulated.This empirical analysis suggests that the rise of private business has gone a long way toward turning China (starting with her industrial sector)into a market economy.In short,the reversal of the formerly distortion-laden path appears to be decisive and is being led by widespread —and healthy (i.e.in terms of profits)—privatization of the economy,which is in turn leading to improved allocation of production and employment.2.Data and measurement

2.1.Uniquely comprehensive microdata

The empirical work carried out in this paper utilizes the industrial firm database of the China National Bureau of Statistics (NBS).These data cover the 1998to 2003period and include all industrial enterprises with annual sales in current yuan of 5million or higher.5Ten percent of firms are excluded in each year from the analysis since they have implausible or zero values for gross output,intermediate inputs,employment or fixed assets,based on criteria adapted from Geng (2004).In 1998,this leaves 140,000firms with valid data,with the number rising to 180,000by 2003.As a result of exit and entry to the database,about 80%of the firms in a given

3

Carsten Holz (2006)has recently directly contested Young's main findings and their interpretation —particularly the extent to which they imply rising trade barriers in the mid-1990s.Naughton (2003)also found less evidence of barriers between Chinese provinces than Poncet in the pre-1992period.4

Bystr?m,Olofsdotter,and S?derstr?m (2005)also find that interregional integration has increased significantly,judged by co-movement of output shares in the decade to 2001.Viewed in a similar light,Zax and Yin (2005)find that industrial factor prices had essentially reached a plateau in terms of convergence by the 1999–2002period.5

In principle these data also cover state-owned enterprises even if they do not meet the threshold,but this small number of firms were excluded from the analysis.Among all industrial firms below the threshold,we estimate that the share of output by the private sector exceeds 90%(OECD,2005).

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year have a valid observation in the previous year.In order to utilize the maximum number of firm observations,the(unbalanced)panel consisting of all firms with valid data is used in the analysis that follows.

2.2.Financial variables adjusted to be comparable as possible

For each firm,detailed balance sheet data are available(summary shown in Table2),in addition to basic information on its ownership structure,industry,location,and employment.This high level of detail allows for several types of adjustments to be made to value added, intermediate inputs,profit,and capital concepts to correspond more closely with international practice.For instance,Chinese statistical practice includes V AT in value added and interest in intermediate inputs;we exclude them.In computing rates of returns on assets,the preferred profit concept is a national accounts one where bank debt and equity are treated neutrally.Thus,we add interest paid to profits prior to tax and investment income(essentially net surplus).And in measuring capital,we take the book value of net fixed assets plus inventories as an estimate.One drawback to the database is that assets are valued at historic cost and are not revalued.However, over the period1998to2003,the increase in the price index of fixed asset investment was less than1%per year,limiting the potential bias from this source.

Since the data are firm observations,we are able to reclassify firms and their data items based on firm-level ownership structure.This allows us to re-appraise previous estimates of the extent of private ownership in China.Moreover,in the final section where we compute concentration indices,firm-level heterogeneity is taken into account in the computation of the Hoover–Glaeser specialization index and Herfindahl–Hirschman(HHI)concentration ratios can be computed,on the same basis as the U.S.Census Bureau.

3.Ownership

3.1.Definition of private control

According to contemporary theories of the firm,ownership should be defined in terms of which shareholder controls the“residual rights”of the firm,in the sense of who dictates unforeseen contingencies(Hart,1995).This is the definition that we seek to apply.Since detailed data on the shareholding structure of each firm is available,the type of controlling shareholder can be identified.This approach contrasts with the official firm registration categories that are commonly used in analysis of China's business sector.

Rather than using the official firm registration status that is commonly shown in Chinese statistical publications to look at ownership,we separate firms by type of controlling shareholder. By examining shareholding structure,firms can be separated by whether it is the state(directly or indirectly through legal persons),a collective(local government),or a private entity(individuals, domestic legal persons,or foreign companies)that controls the firm.This classification allows us to look at the type of actual owner,since the official registered enterprise structure often does not reflect the type of owner that controls the firm because companies rarely change their registration status,even when their controlling shareholder changes.The use of shareholder information is especially important for limited liability and shareholding companies(dominated by legal person shareholders),whose ownership is heavily mixed between state and private control.

In the NBS microdata,firms directly report whether they are state held:that is,they are controlled directly or indirectly by the state.In order to distinguish between direct and indirect

Table 2

Profile of industrial microdata (all firms meeting criteria)a

1998

1999

2000

2001

2002

2003

Basic data

Units Number of firms 144,112140,559141,956150,948160,969180,146Millions of persons

Employment

59.255.553.051.752.655.5Billion yuan Value added (including V AT)1842.82046.92413.42693.13154.34069.2Value added tax payable 270.4298.6352.0384.8431.6535.4Sales tax and extra charges

121.2128.3140.4151.9172.3202.4Gross output comparable (1990)prices 4946.15242.96170.06861.97978.510,345.4Gross output current prices 6518.56991.18231.49170.210,701.213,879.1Intermediate input 5556.76260.07300.78365.49965.612,591.8Exports

1049.41124.51413.81587.51964.62647.0Income statement Billion yuan Sales Revenue 6168.06713.58090.49008.710,577.513,966.8Cost of sales 5072.55499.16589.27405.68692.711,557.6Sales charge

219.4248.1288.7338.3394.2484.4Sales tax and extra charge 121.2128.3140.4151.9172.3202.4Sales profit

754.9838.11072.21112.91318.21722.4Other business profits

41.336.345.047.952.369.8Administrative fees and charges 466.6487.0541.9572.6640.9780.1Memo:R&D –––26.234.943.8Financial charges

232.5210.3188.9181.6192.7206.9Memo:interest outlay 214.4194.5177.8168.2172.8181.7Operating profit 97.1177.1386.4406.6536.9805.1Subsidies

27.627.532.535.138.346.5Investment income and adjustments ?16.7?19.2?8.4?21.2 4.530.1Profit b

141.4223.8427.3462.9570.7821.5Tax on profits 51.160.674.987.0108.6141.3Dividends

56.263.087.696.2114.3–Retained earnings 34.0100.1264.9279.7347.8–Balance sheet Billion yuan Assets

7367.97843.48291.38902.09569.910,947.8Net fixed assets 4117.44516.44909.85231.75657.06406.4Inventories

1470.91470.31557.01642.81743.22040.4Deferred and intangible assets 1779.61856.71824.62027.42169.72501.0Liabilities

7367.97843.48291.38902.09569.910,947.8Long term liabilities 1951.32005.52065.82053.42119.12319.3Net short term liabilities 1612.21547.41472.91506.31585.11787.9Equity

3768.94241.54694.35280.75816.36755.8

Performance indicators

Profit plus interest c

as a percent of fixed assets plus inventories

Rate of return on physical assets 6.1 6.79.28.910.112.2Profits as a percent of equity

Rate of return on equity 3.8 5.39.18.89.812.2Billion yuan

Profit plus interest c

339.1399.1596.7609.8748.01033.3Net fixed assets plus inventories 5588.35986.76466.86874.57400.28446.8Percent of net fixed assets

Depreciation rate

–8.18.18.58.79.3

Source:China National Bureau of Statistics with joint NBS-OECD analysis.

a

Missing observations and those with inconsistent data are not included.b

Referred to as “Total Profits ”in most Chinese publications.c

Excludes investment income.

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control,firms where the state owns more than50%of the share capital6are classified as directly state controlled,with the remainder of state-held firms treated as indirectly controlled(by legal persons or other shareholders).Amongst the non-state held firms,collective controlled firms are identified if they report collective capital share greater than50%.The remainder of the non-state firms are subdivided among various types of private ownership depending on whether they are controlled(share capital greater than50%)by a private company(a non-state legal person), individuals,non-mainland agents,or other shareholders.This classification by controlling share-holder—which is exhaustive—allows us to look at the type of actual owner,since the official registration status often does not reflect the de facto owner.The use of controlling shareholder also overcomes the difficulties in interpreting the bewildering array of different ownership registration categories,many of which are not meaningfully distinct.See OECD(2000)and ADB(2003)for a detailed list of the legal basis for each enterprise type.

3.2.Results

The result of this exercise is to show a rapid shift toward private ownership in China amongst firms with more than5million yuan in annual sales(Table3).Classification by controlling shareholder shows that the private sector has grown from27.9%of industrial value added in1998 to52.3%in2003.Individually-controlled firms'share has grown most rapidly,representing almost half of this increase,with the remainder of the gain split equally between private companies(controlled by non-state legal persons)and non-mainland shareholders.Part of this increase may be attributed to the progressively larger share of all firms that have had to report to statistical authorities over the years,since most of the firms that have crossed over the reporting firm size threshold appear to be private.7

At the same time as the private sector has grown,the state and collective controlled sectors have fallen.The share of value added directly controlled by the state fell from38.9%to22.9%over the 5years1998–2003.While several percentage points of this drop may represent a shift toward indirect state control,the remainder occurred through the closure,restructuring,and privatization of enterprises.The collective controlled share has also fallen rapidly,as many of these firms have also exited or changed ownership.

Defining ownership based on control can differ significantly from the registered ownership categories that are usually relied upon.For instance,more than half of limited liability companies' value added was controlled by private shareholders in2003,as was a quarter of shareholding companies and joint ownership enterprises'value added.Many such corporations were formerly state controlled and since have been privatized.In many studies,such companies are assumed to either lie completely in the public or the private sectors(see ADB,2003;IFC,2000;Song,Tenev, Yao,&Garnaut,2005).

Even within registered ownership categories that should be more homogenous,there is a range of controlling interests.For example,although all structures classified as state-owned enterprises and solely state-funded corporations are controlled by the state in some way,over20%were indirectly controlled by other state controlled companies(through legal person shares).And while 6There are drawbacks to such a classification.Share ownership is only one of the criteria that the proposed revision of the System of National Accounts(SNA)suggests as relevant.In particular,the SNA suggests looking at groups that control the board of directors.It may be possible to exert control through the board with less than50%of the share capital.

7Nevertheless,a generalization of these results to the whole commercial business sector and to aggregate GDP confirms a rapid shift toward private ownership,with it overtaking public ownership during the past5years(OECD,2005).

Table 3

Mapping of official registration status to type of controlling shareholder

Type of controlling shareholder (row percent)

State controlled Collective controlled

Private controlled

Private Subtotal

Total Column percent Direct

Indirect

State N 50%LP N 50%Other Collective N 50%LP N 50%Individual N 50%Non-mainland N 50%

Other

(2003)Memo:1998

Official registration status a State-owned enterprise

73.618.48.00.00.00.00.00.00.010013.837.3Collective-owned enterprise 0.10.2 1.161.618.114.2 1.0 3.636.9100 6.318.3Joint ownership enterprise 45.911.6 4.312.714.17.10.1 4.225.51000.7 1.1Solely state-funded corp.80.315.1 4.60.00.00.00.00.00.0100 5.0 3.9Other limited liability corp.19.714.2 5.5 6.225.224.90.6 3.754.410014.1 3.6Shareholding corporation 26.427.419.9 2.010.610.10.6 2.924.310015.07.1Cooperative enterprise 1.2 1.0 1.815.622.650.6 3.8 3.380.3100 2.2 3.1Private firm

0.00.10.1 2.725.169.1 1.1 1.797.110013.3 2.7Other domestic firm 1.6 2.00.012.737.037.5 3.3 5.983.71000.10.1Non-mainland J.V .b

9.110.210.4 3.016.0 4.841.5 4.967.310017.616.8Solely non-mainland firm b 0.00.00.70.1 1.60.595.6 1.499.210012.0 5.9Overall (2003)

22.911.37.2 6.413.317.219.2 2.652.3100100

Memo:overall —1998

38.9

10.3

5.6

17.3

7.4

5.8

12.6

2.1

27.9

100

100

By percent of firms'value added,2003.

Source:China National Bureau of Statistics industrial microdata with joint NBS-OECD analysis.a

Official registration status is based on the legal form used when the company was set up.See OECD (2000)and ADB (2003)for a more detailed list of the legal basis for each enterprise type.b

Non-mainland (joint ventures and solely-funded firms)is an aggregation covering investors from,Hong Kong,China;Macao,China;Chinese Taipei and all other economies.

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firms officially registered as private and solely-foreign funded were overwhelming controlled by private shareholders(over97%),almost a third of firms registered as non-mainland joint ventures, on the basis of value added,are actually controlled by the state.

The structure of the private sector has become increasingly diversified across industries as well.8In the industrial sector,the state remains dominant only in mining and utilities.In1998,the private sector produced the larger share of value added in only5out of23“non-core”manufacturing industries.9By2003,this was true for all23of these industries.Moreover,in half of them,private firms produced more than three-quarters of output.Overall in these23industries, the private sector employs two-thirds of the labour-force,produces two-thirds of these industries' value added and accounts for over90%of exports.Over a quarter of all industrial output is now produced by private foreign-owned companies,notably in the telecom equipment industry. Domestic private firms have expanded the most in textiles and steel.

The growth of the private sector has not been even across the country.An overwhelming share of private industrial output is produced in the eastern coastal region(Zhejiang,Guangdong,and Jiangsu provinces),that has been at the forefront of all types of reforms.In this region the share of industrial value added from the private sector is63%against only32%in other regions.These other regions are about5years behind in the development of the private sector.However,the central,western,and north-eastern regions'private sectors have been growing faster than the coastal areas'over the5years to2003,suggesting that catch-up is underway.

To date,the emergence of the private sector has been concentrated amongst small and medium enterprises,with private entities controlling81%of the firms in the dataset with under1000 employees,compared with only36%of firms with over1000employees.There is evidence that an increase in the average size of a private sector company could enhance productivity,but private firms face obstacles to increase scale.This situation is symptomatic of the overall insufficient level of concentration in some industries.

4.Productivity

4.1.Production function estimates

In order to determine the extent to which the ownership transformation has resulted in improvements in productivity,production functions are estimated at the firm level using the microdata.Several specifications are used to ensure that the results are robust.Cobb–Douglas production functions are specified in both value added and gross output forms,to ensure robustness,since each form can yield different results(Bartelsman&Doms,2000).Wage-augmented variants are used in the preferred specification due to concerns about the quality of the measure of employment(total headcount),and the presence of large wage gaps across different types of firms.These gaps suggest that private firms either hire much more qualified workers or they utilize higher wages to deter shirking and improve incentives using efficiency wages(see Akerlof&Yellen,1986).The value added form is thus specified as:

VA?A d L a1d K a2d W b d e D d g1d e O d g2d e ee1T8Refer to Annex Tables2.A2.3and2.A2.4in OECD(2005).

9The excluded manufacturing industries are petroleum,smelting,tobacco,and transport equipment.These industries are a subset of the“core”sectors where the state continues to dominate(ibid).

Where V A is value added (pre-tax,deflated using the implicit gross output deflator),L is labor input (in full time equivalents),K is capital stock (based on book value of net fixed assets),W is relative wage (mean-differenced),and matrix D is a set of control dummies for scale,time,region,and industry;εis the (exponential)error term.The matrix O of dummy variables represents the various forms of ownership described in the previous section,and corresponds directly to the types of controlling shareholder shown across the columns of Table 3.No dummy has been introduced for the group of enterprises directly controlled by the state.The equation is transformed into log-linear form:

ln eVA T?a ta 1ln eL Tta 2ln eK Ttb ln eW TtD d g 1tO d g 2te

e2T

This equation is then estimated for the entire dataset with controls for two-digit industries and regions,using ordinary least squares (OLS),with White heteroskedasticity-consistent standard errors.It was also estimated in log differences (growth rates)and using a two-stage least squares (2SLS)estimator with lagged values of the independent variables as instruments.Coefficients on O can be directly interpreted as differences in productivity for each ownership type,relative to directly state controlled firms,that interests us.The gross output form is estimated similarly:

GO ?A d L a 1d K a 2d M a 3d W b d e D d g 1d e O d g 2d e e

e3T

The gross output equation is then transformed into log-linear form,with the terms analogous to Eq.(2)above.The additional input M is intermediate inputs (deflated using the materials of production deflator).

In order to ensure the robustness of the results,the gross output equation was estimated in both levels and growth rates separately within each two-digit industry using four-digit industry controls,using both OLS and random-effects panel estimators (which were not used on the overall dataset due to computational limitations).10The results,which allowed the production function coefficients to vary by sector,yielded differences in the ownership categories that were highly consistent with those shown in the overall OLS results,and indeed,even the capital coefficients were significant throughout,suggesting the results were unlikely to be affected by potential simultaneity problems (see Griliches &Mariesse,1995).

In the estimations that follow,the exponential of the coefficients on the dummy variables can be directly interpreted as percent differences in the constant term,total factor productivity.Thus,differences in productivity (in levels or growth rates)between directly state controlled companies and various forms of non-state control are simply the exponential of the estimated coefficients.

The literature on firm ownership argues that firms controlled by private shareholders should have stronger profit incentives and higher productivity than those owned by government.Firms owned by governments typically suffer from weak or distorted incentives,best illustrated by the existence of soft-budget constraints,where expectations of bailouts by the state creates moral

10

A fixed effects panel estimator could not be used due to the inability to adequately match firm observations across the entire 1998to 2003period.The NBS does not assign permanent firm identifiers,and even a change of name or basic ownership structure would typically cause the firm identifier to change.As a result,a balanced panel would contain only 15%of the 307,117firm observations with unique identifiers.However,in adjacent years,about 80%of firms could be matched.Therefore,we chose to focus on the difference,or growth rate,equation as a means of considering firm-level effects,since fewer name and structure changes occur in any pair of adjacent years,compared with the whole sample period.

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hazard problems,thus leading to chronic underperformance.Studies of the Chinese economy have found that collectives often out-perform state-owned enterprises as a result of harder budget constraints,but fewer studies have been carried out for the private sector(e.g.,Wu,1996; Jefferson&Su,2005).Partial privatization,with the state retaining a controlling interest,has been shown to have some positive benefits,but the evidence here is more mixed(OECD,2005). Further complications in assessing the role of private ownership arise as a result of possible selection biases in the privatization process,which can affect observed performance differences. However,meta-studies have shown that once these biases are controlled for,private owners systematically outperform state owners(Megginson&Netter,2001),although significant delays can sometimes be observed(Brown,Earle,&Telegdy,2006).

Selection biases could be a problem in the case of an enterprise that started under one form of control and later shifted to another,selectively.Each of our enterprise-year observations has controlling ownership detail,but we cannot accurately match firms before and after conversion. Nevertheless,we would only expect selection biases to be an issue for firms which underwent some type of conversion—principally from direct state to indirect state or private legal person controlled firms.It is possible that the best,or worst,performing firms were privatized first. However,since we find below that the estimated coefficients for various types of private firms are all very similar,and robust to the various specifications,selection bias does not appear to be a serious problem.In particular,the results of the2SLS level and OLS difference equation estimates show strong differences between private and state ownership,suggesting that selection biases are not affecting the results.

4.2.Results

The overall means of the data suggest that the movement of factors of production to the private sector has improved economic performance,as the sector is more efficient than the state controlled sector.While labour productivity in the private sector,outside resource-based industries,is nearly the same as in the state sector,the state sector uses almost twice as much capital per worker.Put another way,capital intensity in the private sector is one-third that of the public sector as a whole but labour productivity is just15%less.Efficiency may not be the sole factor influencing productivity;other factors than capital intensity such as the choice of location or industry,types of inputs or production processes,scale of production,or even the age of a firm might influence overall productivity,and a full analysis needs to take their impact into consideration.

4.2.1.Private firms are more productive

Regression estimates with controls for these factors confirm the superior performance of the private sector.Eq.(2)is estimated using OLS,yielding estimates of total factor productivity(TFP) for firms controlled by different types of shareholders.The result confirms that overall productivity is markedly higher in private sector companies,whether they are owned by non-mainland shareholders,other private sector companies or individuals.As shown in Fig.1,on the basis of a value added measure of output,TFP in private sector companies,after taking into account the impact of firm size,location,and industry,is double that in directly state controlled firms(90%to123%higher).Reforms that have changed the nature of state control over enterprises,by allowing control to be exercised indirectly—through other companies—have boosted productivity.These indirectly state controlled firms are about50%more productive. While it is possible that selection biases may affect estimates for firms that have converted from state to private ownership forms,the uniformly large differences in performance for all types of

private enterprises,including those that have not converted from other forms suggests that this is not a problem.11

The estimated equation appears to be quite robust,with a 56%adjusted R -squared,and highly significant coefficients on all terms,including capital (Table 4).In order to ensure that the

11

This result is consistent with those of Jefferson and Su (2005)and Song et al.(2005),who find that privatization yields considerable productivity benefits for shareholding firms in China,even when compared with a control group of firms that did not undergo

conversion.

Fig.1.Differences in total factor productivity by firm ownership.Relative to directly state controlled (state N 50%),in units of value added.1.See Table 4for full regression parameters.Source :National Bureau of Statistics industrial microdata and joint NBS-OECD analysis.

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estimates are not biased by problems of simultaneity,a two-stage least squares (2SLS)estimator was also used,with first lags used as the instruments.The result is strikingly similar to the OLS result,with the coefficients on the various forms of ownership nearly the same except that the effect of scale appears to be more significant:the total factor productivity of firms with over 1000employees is notably higher than that of smaller firms.

The same equation estimated in growth rates (log differences)shows that productivity is not only higher in private controlled firms,but it is increasing at about 5%per year more rapidly,whether the firm is controlled by private companies (non-state legal persons),non-mainland owners,or individuals.Such rapid growth of productivity implies that the productivity gap increased during the estimation period.These results strongly support the idea that the productivity advantages of private

Table 4

Firm-based value added production function regression estimates a

Levels b Levels (IV)Growth rates b Coefficient

Robust t -statistic

Coefficient

Robust t -statistic Coefficient

Robust t -statistic Regression of log(real value added)c on:log(net fixed assets)0.229212.20.252149.60.06527.3log(employees)

0.632212.60.45474.40.423103.1log(average wage rel.to mean)

0.457201.90.676127.50.20476.5Type of controlling shareholder —relative to direct state control (state N 50%)Indirect state,LP N 50%0.37849.20.30734.00.0060.9Indirect state,other

0.53062.60.51150.10.026 3.1Collective,collective N 50%0.772185.00.764146.10.018 4.2Private,LP N 50%

0.792172.40.776135.10.04810.1Private,individual N 50%0.734171.10.737138.40.05412.4Private,non-mainland N 50%0.654124.00.58588.30.05610.4Private,other

0.69486.90.65066.20.014 1.8Scale —relative to under 51employees 51–100employees ?0.157?36.70.009 1.40.015 3.6101–500employees ?0.216?36.10.1169.90.0287.4501–1000employees ?0.125?13.00.37820.50.0397.7over 1000employees

0.15112.00.799

32.9

0.060

10.8

Time —relative to 1998/1999Year 19990.04510.9Year 20000.14635.70.11623.80.015 3.7Year 20010.24260.30.22448.20.012 3.1Year 20020.32380.50.30666.90.0307.8Year 2003

0.405103.1

0.37382.50.04912.9Dummies for provincial regions Significant Significant Significant Dummies for 2-digit industries Significant Not significant Not significant Dummies for age of firm Significant Significant Significant Constant term

Significant Significant Significant Number of observations (pooled)852,354544,871526,550F -statistic (df =98/97)10,0856759196.48Adjusted R -squared

56.6%57.6% 6.0%Root means squared error (MSE)

1.004

1.0080.822

Differences from comparison group are calculated as exp(coefficient)minus one.

Source:China National Bureau of Statistics (NBS)microdata with joint NBS-OECD analysis.a

Regressions estimated on unbalanced panel of all industrial firms with sales of 5million yuan or higher.b

Estimates use ordinary least squares estimator with White heteroskedasticity-consistent standard errors.c

Value added deflated with gross output constant price deflator.

320S.Dougherty et al./China Economic Review 18(2007)309–334

ownership are not due to (one-time)selection biases since there is substantial ongoing growth of productivity in the three principal types of private controlled firms.12However,the results for indirectly state controlled firms suggest some caution,despite the apparent productivity level advantages,given the large standard error on productivity growth for legal person controlled state

12

The weak productivity growth estimate for the small number of private firms with other “other ”controlling owners is harder to interpret,since we do not have detailed information on their controlling shareholder.The result likely reflects the weaknesses in private firms with overly diversified ownership,such as when there is no single controlling shareholder.

Table 5

Firm-based gross output production function regression estimates a

Levels b Levels (IV)Growth rates b Coefficient

Robust t -statistic

Coefficient

Robust t -statistic Coefficient

Robust t -statistic Regression of log(real gross output)c on:Log (net fixed assets)0.04893.30.04257.80.02423.0Log (employees)

0.08664.20.03212.90.14876.2Log (real intermediates)

0.848862.40.910820.20.635265.6Log (average wage rel.to mean)

0.05559.00.04520.10.06756.9Type of controlling shareholder —relative to direct state control (state N 50%)Indirect state,LP N 50%0.08925.50.05914.40.0010.4Indirect state,other

0.12129.80.08918.10.010 2.8Collective,collective N 50%0.12868.00.07734.00.007 4.0Private,LP N 50%

0.13667.20.08434.50.0157.5Private,individual N 50%0.12163.90.07432.70.01910.6Private,non-mainland N 50%0.08738.60.03512.70.0188.1Private,other

0.12939.10.08421.50.010 2.8Scale —relative to under 51employees 51–100employees ?0.025?14.8?0.005?1.90.009 5.1101–500employees ?0.030?12.20.006 1.30.0138.5501–1000employees ?0.011?2.70.026 3.60.0209.8over 1000employees

0.0377.10.065

6.8

0.028

12.6

Time —relative to 1998/1999Year 19990.004 2.1Year 20000.05632.00.0010.60.04527.3Year 20010.05733.60.04925.60.004 2.5Year 20020.05230.90.04221.60.010 6.2Year 2003

0.09154.8

0.07238.9

0.045

28.3

Dummies for provincial regions Significant Significant Significant Dummies for 2-digit industries Significant Significant Significant Dummies for age of firm Significant Significant Significant Constant term

Significant Significant Significant Number of observations (pooled)879,720559,293553,620F -statistic (df =99/98)62,28645,5741609.83Adjusted R -squared

91.7%92.4%60.0%Root means squared error (MSE)

0.417

0.408

0.345

Differences from comparison group are calculated as exp(coefficient)minus one.

Source:China National Bureau of Statistics (NBS)microdata with joint NBS-OECD analysis.a

Regressions estimated on unbalanced panel of all industrial firms with sales of 5million yuan or higher.b

Estimates use ordinary least squares estimator with White heteroskedasticity-consistent standard errors.c

Value added deflated with gross output constant price deflator.

321

S.Dougherty et al./China Economic Review 18(2007)309–334

322S.Dougherty et al./China Economic Review18(2007)309–334

firms in the difference equation.Similarly,productivity growth for collective controlled firms also appears to be rather meagre,despite their high productivity levels compared to private firms.

4.2.2.Alternative production function

The gross output form of the production function is also estimated using OLS and2SLS, yielding results that generally support those found using the value added specification(Table5). Privately controlled firms have significantly higher productivity than those controlled directly by the state,and their rate of productivity growth is higher.

Results using the gross output specification are not directly comparable with those using the value added specification due to the intermediate content and its close association with gross output.Consequently each of these equations has a much higher adjusted R-squared.Despite the difference in output concepts,the gross output coefficients are roughly comparable with those for value added when divided by one minus the coefficient on intermediate inputs.The result suggests that perhaps as much as20%of the productivity differential observed using the value added specification may be due to differences in the utilization of intermediate inputs. Nevertheless,this still leaves more than80%of the productivity differential remaining.

A further sensitivity test is employed by estimating the full gross output production function separately for each of the34individual two-digit industry categories with sufficient observations, using four-digit,rather than two-digit,industry controls,and otherwise the same input and dummy variables.While there were some differences across industries,in32of34industries, privately controlled companies performed significantly better than those controlled by the state. Moreover,the average(weighted)coefficient on private ownership was slightly higher than what was estimated using OLS for the industrial sector as a whole.Similar results were also found in estimates using a random-effects panel estimator at the industry level.

4.2.3.The wage term

The wage term in the production function is included to address concerns about the quality of the labor input measure and the possibility that firms use efficiency wages as a means to improve incentives.Its inclusion has only a minor effect on the estimated productivity advantage attributed to private ownership.In the gross output specification,if the wage term is dropped,the productivity advantage on private control is marginally lower,but in the value added specification,the productivity advantage associated with private control is slightly higher.However,the effects of removing the wage term on the overall equation are more substantial.In particular,without the wage term,the coefficient on labor input declines by a large amount,while it increases on net fixed assets.Moreover,the adjusted R-squared drops appreciably under the value added specification. Given the stronger explanatory power of the equations that include the wage term,and previously observed wage efficiency behavior in non-state-owned enterprises in China(see Fleisher&Wang, 2001),our preferred specifications shown above include the wage term.

5.Profits

Over time there is evidence of across-the-board gains in productivity,as industries became more competitive and under-performing companies exited or were restructured.Not all of the increase in productivity seen in the industrial sector has resulted in lower prices.There was a substantial increase in the profitability of Chinese industrial enterprises during the period1998to 2003,amounting to over four percentage points of GDP.Gains in productivity have occurred even in the segment of the publicly-controlled sector that is directly controlled by the state,with gains

in firm productivity corresponding quite closely in time to improvements in the rate of return on assets,suggesting a strong pass-through of efficiency gains to profitability.While we do not have enough time series observations to analyze the relationship between profitability and productivity in a regression framework,we are able to use the microdata to decompose the contributions of various factors to the increase in profitability,as well as to examine the distribution of profits across the spectrum of state and private controlled firms.5.1.Decomposition of profits

Rates of return on assets and equity are computed for each of the ownership classes that we identify.These rates of return are then decomposed into subcomponents to better understand how they have changed over the 1998to 2003period.The rate of return on assets (ROA)is computed as:

ROA ?GOS VA VA Cap ?

Dep

Cap e4TWhere GOS is the gross operating surplus,or profits before deduction of interest,tax,and

depreciation;V A is value added on a national accounts basis (including interest),Cap is the value of net fixed capital at book value plus the value of inventories,Dep is accounting-based depreciation.The changes over the 1998to 2003period are decomposed into:

D ROA ?D Gross operating margin ?D Capital output ratio ?D Depreciation rate

e5T

Table 6

Financial operating indicators

1999

2000

2001

20022003State controlled

Percent of industrial value added Earnings before interest,depreciation and taxation 51.459.256.256.859.4Depreciation 28.126.327.626.624.8Interest 15.311.810.39.57.6Profit

7.921.118.420.627.0Profit plus interest a 23.232.928.630.234.6Capital output ratio 3.8 3.5 3.5 3.3 2.9Inventory output ratio

1.00.90.80.80.7Intangible and deferred assets ratio 1.7 1.3 1.4 1.3 1.1Total capital 6.4 5.7 5.7 5.3 4.7Privately controlled

Earnings before interest,depreciation and taxation 37.339.437.938.337.6Depreciation 15.213.513.112.511.6Interest 7.9 6.3 5.2 4.4 3.8Profit

14.219.519.621.522.2Profit plus interest 22.225.924.825.826.0Capital output ratio 1.8 1.6 1.5 1.4 1.2Inventory output ratio

0.80.70.70.60.6Intangible and deferred assets ratio 0.60.60.60.60.6Total capital

3.2

2.9

2.7

2.6

2.4

Source:China National Bureau of Statistics industrial microdata and OECD calculations.a

Net surplus,excluding investment income.

323

S.Dougherty et al./China Economic Review 18(2007)309–334

The change in the gross operating margin comes from the partial derivative of the GOS/V A ratio;the second term,the change in the capital –output ratio comes from the partial derivative of the V A/Cap ratio;and the third term,the change in the depreciation rate,comes from differences in the Dep/Cap ratios.The contribution of each ratio over the elapsed period is calculated for each class of ownership.13Financial data come from the balance sheets of companies that meet the quality criteria.5.2.Results

A first look at the profit data suggests that gains in productivity have fed through to profits,in both the private and public sectors.In the face of increasing liberalisation and market competition,private companies have been able to maintain earnings before interest,depreciation and tax at a fairly constant share of their value added (Table 6).Growing TFP has allowed declining capital output ratios and a fall in depreciation charges even though the speed with which assets were written off increased.As a result,the net operating surplus of private industrial companies increased as a share of value added,bringing an even more marked increase in rates of return on physical capital.Financial indicators for state controlled industrial companies show that they have made significant improvements in performance from their relatively low level at the end of the 1990s (see OECD,2000).The improvements shadow those made in the private sector,but at a dampened pace.Earnings before interest,depreciation and taxation have increased as a share of value added.The modest improvements in total factor productivity have allowed depreciation charges to fall,in spite of a rise in the rate at which assets are written off.As a result,net operating surplus has risen markedly,bringing about a near-doubling in the rate of return to physical assets.5.2.1.Decomposition shows shifts in capital driving changes

The decomposition of the rates of return on physical assets shows that a large part of the increase in profitability has come about through changes in the capital –output ratio that reflect

Table 7

Decomposition of rates of return on capital

1998

Rate change due to increase in 2003

Rate of return on physical capital

Profit margin Capital –output ratio Depreciation rate Rate of return on physical capital Rate of return on physical assets a All enterprises

6.1+2.1+5.3?1.312.2State controlled companies

4.8+3.6+3.3?1.610.2Controlled directly by the state 3.9+2.9+2.8?1.48.2Controlled by state held companies 7.4+

5.8?0.9?0.611.7Other forms of state control 8.5+3.4+

6.0?2.315.6Collectively controlled 11.1+0.2+5.5?0.416.3Private companies

7.8+1.2+6.7?0.715.0Non-mainland controlled 4.7+2.9+8.3?1.314.5Controlled by individuals

12.0+0.4+4.6?1.016.0Controlled by non-state companies

8.6

+2.8

+2.1

?0.5

13.0

Source:China National Bureau of Statistics industrial microdata and OECD analysis.a

Rate of return on physical capital calculated as operating surplus divided by fixed assets and inventories.

13

The exact formula used is:D ROA ?D GOS VA VA P Cap P

tD VA Cap GOS

P

VA

P ?D Dep Cap .324S.Dougherty et al./China Economic Review 18(2007)309–334

improvements in the allocation and use of capital (Table 7).In part this is because of the gains in productivity,but more broadly this may reflect an increasingly market-based allocation of capital by state,collective,and especially private controlled companies.This change was likely motivated by an easing of pricing pressures from the exit of debt-ridden companies with low or negative rates of return that effectively held down margins.Indeed margins have improved in the period 1998to 2003.This improved allocation of capital is also reflected by the increase in regional concentration indices and specialization without large increases in industry concentration levels,as described in the next section.

Differential rates of return on assets for firms with different types of state control suggest that ownership restructuring has had an important role in improving state controlled firm performance.Return on assets for firms with state legal person controlling shareholders (i.e.indirectly state controlled firms)have fluctuated,but in the last 2years were nearly 50%higher than those with direct state control.There are a small number of firms (1%of all firms)where the state controls the company through a large minority stake.These companies performed even better,so far as to exceed the returns on assets for private enterprises in 2003.

5.2.2.Changes are not even across the distribution

There has also been a slight reduction in the proportion of private companies making losses,from one in six to one in seven.14At the other end of the earnings distribution,almost a quarter of private companies earned a rate of return of over 25%in 2003and almost 30%of companies had no net debt.Most impressively,private companies controlled by domestic individuals and companies have even better ratios than those controlled by non-mainland

agents.

Fig.2.Distribution of rates of return.Private and state controlled firms.Source :China National Bureau of Statistics and OECD estimates.

14

This proportion compares favourably with that of loss-makers among listed companies in OECD countries (one in five,or about 20%in 2002).In contrast,one in three state controlled companies in China made losses in any given year.

325

S.Dougherty et al./China Economic Review 18(2007)309–334

Improvements in the rate of return have not been even across all state controlled companies, even though they have been fairly widespread across industries.15The biggest improvements have come from the upper end of the distribution,where the top20%of state controlled firms contribute over80%of the net overall increase in returns,with the remaining improvements spread across the low end of the distribution(Fig.2).However,changes in the middle of the distribution have been quite modest,with the rate of return for the median firm remaining in the 1%to2%range,and the proportion of loss-making firms declining from42%in1998to35%in 2003.Overall,two-thirds of state held firms in the industrial sector earn less than a5%rate of return on assets prior to payment of interest.

The poor financial condition of the lower tail of firms illustrates the remaining depth of problems.Nearly15%of state controlled industrial companies trade with negative equity funds. The long tail of the distribution of performance means that a significant group of state firms are insolvent despite improvements in the aggregate state sector indicators.For many,returns on assets are also negative suggesting that even conversion of debt to equity would not save them. Restructuring appears to be a partial solution,but many will need to go through the insolvency process that is being strengthened.

6.Restructuring

https://www.sodocs.net/doc/085976319.html,putation of concentration indices

In order to assess the degree to which enterprise restructuring is facilitating improved specialization and comparative advantage,several indices of concentration are computed.The first is the Balassa–Hoover Index,which measures the extent to which an industry is specialized by region, with higher vales of the index reflecting greater specialization in an industry(Hoover,1936).It is based on the location quotient L with respect to output,neatly described by Bai et al.(2004)at time t:

L ij?Y ij=Y i

Y j=Y

e6T

Where Y ij is output of industry i in region j,Y j is total output in region j,Y i is total output in industry i,and Y is total industrial output.If L ij is greater than1,then region j has a higher percentage of industry i than of total industrial output.The regions j are arranged in order of increasing location quotients(degree of specialization)in an industry i and cumulated.A Gini index is then computed of the resulting area between this curve and the45°axis,resulting in a value for the Balassa–Hoover index for each industry.This value is by definition between0and1, with a higher value representing greater specialization by region.In order to yield an overall index,the index for each industry is then aggregated weighting by the industry's share in total output.This index is also computed using employment data in place of output data(defining Y as employment rather than output).These computations are done at the two-digit industry level among provincial-level regions,for each year in the dataset.

An alternative regional concentration index that controls for the size distribution of firms is also computed,taking advantage of the firm-level data available in this study.This index,the Ellison–

15While state controlled companies in the core industries had the largest increase in profits and are about50%more profitable,overall state ROA increased significantly from1998to2003in all but the most competitive industries (garments,electronics and telecom equipment).

326S.Dougherty et al./China Economic Review18(2007)309–334

Glaeser Index,yields a measure of regional concentration by industry that includes an adjustment for intra-firm heterogeneity (Ellison &Glaeser,1997).This index γis defined at time t as:

g i u

G it =1?X

j

s 2jt !

?H it

1?H it

e7T

Where the term G it is the sum of squared deviations of the industry i 's employment shares s ijt

from a measure,s jt of region j 's share of aggregate employment:16

G it u

X

j

es ijt ?s jt T2

e8T

And the term H it is a Herfindahl-style measure of the firm-level concentration of employment in an industry:

H it u X k

e 2kt =

X k

e kt !2

e9TWhere e kt is the level of employment in the k th firm in industry i at time t .These measures are computed at the three-digit industry level among provincial-level regions.They are then weighted up to the aggregate level using both firm and employment

weights.

Fig.3.Indexes show increasing regional specialization of industry.Note:The ‘BH ’index refers to the Balassa-Hoover index;the ‘EG ’index refers to the Ellison-Glaeser index.Source:China National Bureau of Statistics industrial microdata and joint NBS-OECD analysis.

16

Following Dumais,Ellison and Glaeser (2002),we define s jt as the unweighted arithmetic mean of the s ijt terms across the industries in the sample,s jt ?e1=I TP I s ijt ,where I is the total number of industries.

327

S.Dougherty et al./China Economic Review 18(2007)309–334

Finally,in order to assess the degree of market concentration in an industry,the Herfindahl –Hirschman Index (HHI)is also computed:

HHI ?

X N i ?1

e100d s i T2

The index is defined as the sum of the squared market shares s i of each firm i in an industry.

Industries for which the HHI index is greater than 1800are considered by the U.S.Department of Justice to be highly concentrated,while those over 1000are considered to be moderately concentrated (USDOJ-FTC,1992).An alternative version of the index is also computed using the U.S.Census Bureau approach,which only considers the largest 50firms (N ≤50).6.2.Results

The results of the productivity analysis section show that the ongoing privatization of the economy is driving a dramatic transformation of its productive potential and profitability.However,they do not give an indication of the aggregate implications that restructuring has had on the allocation of production across industries and regions.Previous analysis of regional specialization suggests that in the period from the late 1980s to 1997,specialization followed a J-shaped path,with relatively rapid improvements in the mid-1990s (Bai et al.,2004).We extend these results —which suggest that this process has continued —using computations from the National Bureau of Statistics industrial microdata from 1998to 2003.

6.2.1.Growing regional concentration of production

The Balassa –Hoover Index is been calculated across 38industries and 30provincial-level regions using the data on the 160000to 180000firms that appear annually in the micro-

Table 8

Regional concentration indexes

1998

1999

2000

2001

2002

2003

Balassa –Hoover Index Gross output-based Simple average 0.3180.3280.3370.3420.3480.347Output weights 0.3120.3240.3310.3400.3420.347Employment-based Simple average

0.3140.3190.3280.3370.3530.358Employment weights 0.286

0.295

0.315

0.327

0.338

0.347

Ellison –Glaeser Index Employment-based Simple average ?0.2174?0.1862?0.0503?0.0570?0.0479?0.0356Firm weights

?0.0089?0.0088?0.0069?0.0065?0.0060?0.0046Employment weights ?0.0053?0.0056?0.0045?0.0041?0.0038?0.0030Memo:a

Mean G 0.001170.001060.001090.001030.001190.00135Mean H 0.007470.007430.007460.007080.006890.00583G ?H

?0.00630

?0.00637

?0.00637

?0.00605

?0.00570

?0.00448

Source:China National Bureau of Statistics industrial microdata and OECD analysis.a

G and H refer to the mean across industries of Eqs.(8)and (9),respectively.

328S.Dougherty et al./China Economic Review 18(2007)309–334

私车公用协议-(完整)

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员工私车公用协议模板

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1、乙方将该车辆用于公司事务使用时，享有第二条第2款中相应费用报销的权利。 2、乙方应提供驾驶证、车辆行驶证、保险单等有效证件并保证在协议期间的真实有效性以及车况的完好。 3、乙方在使用该车辆时应严格遵守交通规则和相关法律法规，谨慎安全驾驶并及时维护保养； 4、乙方在使用该车辆期间造成的任何侵权责任（含交通事故），均由乙方承担责任。 四、乙方应在签订本协议的同时，提供身份证复印件、驾照复印件和车辆行驶证复印件各一份，供甲方留存。 五、本协议签订前，乙方已完全理解本协议的全部内容，签订本协议是乙方的真实意思表示，乙方同意按本协议约定内容使用车辆。 六、本协议有效期年，自年月日至年月日止。 七、协议的终止及解除 1、协议期间，因车辆状况或其他原因使车辆无法为甲方提供服务的，甲方有权单方解除协议；乙方更换服务车辆应另行签署协议，另行签署日起本协议自动终止。 2、如甲乙双方在使用期届满时未达成延长使用期协议，则该协议自动终止。 3、乙方离职，此协议随同离职生效日终止。 4、协议期内，甲乙双方如有特殊情况需提前解除协议，需提前一周提出解除本协议。 八、本协议经双方签字或盖章后生效，若有其他未尽事宜，由双方另行协商解决。 九、本协议一式两份，甲乙双方各执一份。 甲方（盖章）：乙方（签字）：

员工车辆私车公用协议书

员工车辆私车公用协议书 甲方（员工）： 乙方（公司）： 甲、乙双方本着自愿平等的原则，经协商一致，特签订本协议，以兹共同遵守。 一、本协议书适用于因工作原因，甲方将自有私车提供给乙方用于各项工作使用之情形。 二、车辆基本情况 1.车辆产权为甲方所有，车牌号； 2、车辆状况为：良好，年检合格； 3、车辆具备登记证书、行驶证、保险合同，年检合格证等相关证照。 三、车辆租用 1.甲方同意将车辆提供给乙方用于工作。 2.乙方根据工作需要使用甲方车辆时，只能由甲方本人驾驶，因此而产生的燃油费、通行 费、路桥费等按乙方财务制度报销。 3.私车公用补贴：协议期限内乙方按每月0元补贴给甲方，与工资一并发放。 4.车辆的保管和维护修理由甲方负责； 5.甲、乙方在使用车辆时，必须严格遵守国家交通法律法规，违章驾驶所产生的一切后果， 由甲方全部承担； 6.如遇车辆驾驶过程中发生交通肇事，按照当地公安交通管理部门出具的《交通事故责任 认定书》，甲、乙双方各自承担相关法律责任。若由于甲方在工作时间内，发生的重大交通事故，甲、乙双方协商处理相关赔偿事宜。 四、车辆租用期限 本合同有效期一年，期满可以续签，期满前甲方离职或书面通知乙方，本合同终止。合同终止，双方互不承担违约责任，乙方应及时、完好的返还甲方车辆。 五、甲方责任 1.保证所提供的车辆具有合法性，并能满足正常工作的需要。 2.服从公司工作安排，合理、合法使用车辆，及时处理车辆的违章及肇事事故等。 3.甲方必须为租赁车辆投保以下险种： （1）机动车交通事故强制责任保险； （2）商业险，其中应当包括第三者责任险、车损险。 六、乙方责任 1.按照合同约定合法使用车辆。 2.报销甲方使用车辆而发生的燃修费、过路过桥费。 七、其它 1.本协议经甲、乙双方签字加盖公章后生效； 2.当甲方车辆年检到期，甲方没有及时年检或无法年检通过，本合同立即终止，乙方及时 返还车辆； 3.本协议未尽事宜，甲、乙双方可另行协商，签订补充协议。补充协议与本协议具有同等 法律效力； 4.如产生纠纷，甲、乙双方友好协商，协商不成的交由有乙方所在地人民法院裁决； 5.本合同一式二份，甲方执壹份，乙方执壹份。 甲方（签字）：乙方（公章）： 本协议签订日期： 1

员工车辆私车公用协议书

员工车辆私车公用协议书 一、本协议书适用于因工作原因，甲方将自有私车提供给乙方用于各项工作使用之情形。 二、车辆基本情况 1.车辆产权为甲方所有，车牌号； 2、车辆状况为：良好，年检合格； 3、车辆具备登记证书、行驶证、保险合同，年检合格证等相关证照。 三、车辆租用 1.甲方同意将车辆提供给乙方用于工作。 2.乙方根据工作需要使用甲方车辆时，只能由甲方本人驾驶，因此而产生的燃油费、通行费、路桥费等按乙方财务制度报销。 3.私车公用补贴：协议期限内乙方按每月0元补贴给甲方，与工资一并发放。 4.车辆的保管和维护修理由甲方负责； 5.甲、乙方在使用车辆时，必须严格遵守国家交通法律法规，违章驾驶所产生的一切后果，由甲方全部承担； 6.如遇车辆驾驶过程中发生交通肇事，按照当地公安交通管理部门出具的《交通事故责任认定书》，甲、乙双方各自承担相关法律责任。若由于甲方在工作时间内，发生的重大交通事故，甲、乙双方协商处理相关赔偿事宜。 四、车辆租用期限 本合同有效期一年，期满可以续签，期满前甲方离职或书面通知乙方，本合同终止。合同终止，双方互不承担违约责任，乙方应及时、完好的返还甲方车辆。 五、甲方责任 1.保证所提供的车辆具有合法性，并能满足正常工作的需要。 2.服从公司工作安排，合理、合法使用车辆，及时处理车辆的违章及肇事事故等。 3.甲方必须为租赁车辆投保以下险种：

（1）机动车交通事故强制责任保险； （2）商业险，其中应当包括第三者责任险、车损险。 六、乙方责任 1.按照合同约定合法使用车辆。 2.报销甲方使用车辆而发生的燃修费、过路过桥费。 七、其它 1.本协议经甲、乙双方签字加盖公章后生效； 2.当甲方车辆年检到期，甲方没有及时年检或无法年检通过，本合同立即终止，乙方及时返还车辆； 3.本协议未尽事宜，甲、乙双方可另行协商，签订补充协议。补充协议与本协议具有同等法律效力； 4.如产生纠纷，甲、乙双方友好协商，协商不成的交由有乙方所在地人民法院裁决； 5.本合同一式二份，甲方执壹份，乙方执壹份。 甲方（签字）：乙方（公章）： 本协议签订日期：青年人首先要树雄心，立大志，其次就要决心作一个有用的人才

私车公用车辆管理制度

私车公用车辆管理制度 第一章总则 第一条目的 为了方便公司各项工作的开展、满足公司车辆资源，提高工作效率，本着有偿使用的原则，结合公司的实际情况，特制订本制度。 第二条适用范围 本制度适用于公司在职的、有私车的员工。 第三条前提条件 1、车辆行驶证、养路费、车辆购置税、车牌、保险单等各种证件齐全； 2、因业务需要外出使用。 第二章审批程序 第四条申请条件 1、拥有私车或者可以借用公司同事车子的员工在符合第三条前提条件后，因公司业务需要，当事人可以提出申请，提交各分管部门领导审批同意后，方可外出。 2、员工确因公务需要使用私车外出时，必须事先填写《私车公用申请及行驶记录月表》（参见附件），列明去向、申请人、车牌号、使用目的、使用时间等相关信息，经审核批准后方可外出。 3、出发前必须向人力行政部门汇报出发前公里数，人力行政部不定期抽查。 4、至少提前一个工作日报准申请，非特殊情况下不允许事后补单。 5、外出车辆必须在下班前开回公司，登记行驶里程数。（如果没有在当天下班前开回公司的处理） 第五条审批流程 1、业务、采购部门 当事人发起流程→部门经理审核→副总助总审核→总经理审核→行政专员→人力行政经 2、财务部门

当事人发起流程→财务经理审核→财务总经理审核→行政专员→人力行政经理 3、行政部门 当事人发起流程→人力行政经理审核→董事长审核→行政专员→人力行政经理 第三章费用报销 第六条费用报销项目 1、私车公用费用报销项目包括：路桥费、燃油费、停车费。 2、停车费、路桥费、燃油费实报实销。燃油费发票抬头必须是公司名，指定的用油型号。 第七条报销标准 1、车辆的维护费和修理费、年检费、保险费均由车主本人承担。 2、行车发生的费用具体根据《私车公用申请及行驶记录月表》每月统一结算。 3、交通违章罚款单据不得核销或变相冲抵。 4、当私车因公外出累计行驶里程超过5000公里时，公司……，数据清零。以此类推。 5、车辆折旧费补贴计算 6、因公外出，私车产生的油耗，补贴标准参见表格 第八条报销程序 1、员工即时填写《私车公用申请及行驶记录月表》→报部门领导审核→每月31日以部门为单位统一报人力行政部稽核→核对无误，当事人填写费用报销单→报部门及分管领导审核→报财务部对费用金额进行核算→报财务总经理批准后。次月10日报销完毕。 第四章违章与事故处理 1、私车公用外出期间严格遵守《交通法》及公司《车辆管理规定》，违章罚款由当事人负责。

XX公司私车公用协议

私车公用协议 甲方： XXX有限公司 乙方： 甲方因工作需要，为提高管理人员的工作效率，允许乙方将本人私车（车牌）______一辆用于甲方的公务活动，经双方协商一致，达成协议如下： 一、使用期限： _____年_____月______日至______年_____月______日。 二、使用方式及租金： 本协议期间，车辆原则上仍由乙方本人保管使用，用于甲方的公务活动；甲方需临时安排时，乙方应服从临时安排。无租金。 三、私车公用规范 （一）乙方必须具备以下条件： 1.乙方依法获得驾驶证，且经甲方安全资格审查合格。 2.乙方提供车辆为乙方本人所有（以车辆登记证书记载为准），已使用年限未超过15年，已办理交强险、第三者险（三者险按照不低于50万元保额标准进行投保）、车损险、乘坐险、不计免赔险等安全保险项目。 3.乙方车辆须是合法手续完备、安全性能良好，能正常使用（以公司技术部审查结果为准）。 （二）乙方车辆由乙方自行保管，自行负责车辆的维修保养及年审等，保证车辆技术状况良好，保证车辆手续合法有效。乙方自行购买路桥年票，乙方自行购买各项保险。乙方车辆每年年审后需重新向甲方提交车辆登记证书、车辆行驶证、保险单等资料原件及复印件。

（三）甲方按月给予乙方定额油料补贴，具体为元、月，由甲方以油卡充值方式支付给乙方。 （四）乙方有下列情形之一的，甲方不再为乙方提供定额油料补贴： 1.乙方车辆使用年限超过15年的。 2．乙方驾驶人和车辆主要信息未到甲方登记，或车辆发生故障、丢失、主要信息改变未到甲方备案的。 3.乙方提供的车辆信息为虚假信息的。 4.乙方无故不使用本人车辆超过5个工作日的。 5.乙方不服从甲方临时安排的。 6.乙方不服从所在部门（基层单位）统筹安排的。 （五）乙方因故当月未使用本人车辆在5个工作日以上的（不含5个工作日），甲方按实际使用天数发放油料补贴。 （六）乙方因在工作时间内驾驶本人车辆办理公务发生交通事故时，应及时向甲方安全监察部报案，由安全监察部协助处理。由乙方进行事故处理并向参保保险公司索赔后，在规定范围内的超出部分费用凭有效凭据向甲方安全监察部申请，核实后，甲方按全责70%、主责75%、同责80%、次责85%、无责和意外100%的比例报销。 （七）乙方车辆在工作时间内办理公务发生交通事故时，有以下情形之一的，甲方不承担事故费用的报销，由乙方自行负责： 1.当事驾驶人存在“酒驾”或“毒驾”。 2.当事驾驶人发生事故后逃逸或私撤现场的，或其他严重违法行为的。 3.若当事驾驶人非甲方安全监察部审核认定的人员的。 （八）乙方应自觉遵守国家《道理交通安全法》等有关法律

XX公司私车公用协议

XX公司私车公用协议 私车公用协议甲方乙方甲方因工作需要，为提高管理人员的工作效率，允许乙方将本人私车（车牌）______一辆用于甲方的公务活动，经双方协商一致，达成协议如下 一、使用期限_____年_____月______日至______年_____月______日。 二、使用方式及租金本协议期间，车辆原则上仍由乙方本人保管使用，用于甲方的公务活动；甲方需临时安排时，乙方应服从临时安排。 无租金。 三、私车公用规范（一）乙方必须具备以下条件1.乙方依法获得驾驶证，且经甲方安全资格审查合格。 2.乙方提供车辆为乙方本人所有（以车辆登记证书记载为准），已使用年限未超过15年，已办理交强险、第三者险（三者险按照不低于50万元保额标准进行投保）、车损险、乘坐险、不计免赔险等安全保险项目。 3.乙方车辆须是合法手续完备、安全性能良好，能正常使用（以公司技术部审查结果为准）。 （二）乙方车辆由乙方自行保管，自行负责车辆的维修保养及年审等，保证车辆技术状况良好，保证车辆手续合法有效。 乙方自行购买路桥年票，乙方自行购买各项保险。乙方车辆每年年审后需重新向甲方提交车辆登记证书、车辆行驶证、保险单等资料原件及复印件。 （三）甲方按月给予乙方定额油料补贴，具体为元、月，由甲方以油卡充值方式支付给乙方。 （四）乙方有下列情形之一的，甲方不再为乙方提供定额油料补贴1.乙方车辆使用年限超过15年的。 2．乙方驾驶人和车辆主要信息未到甲方登记，或车辆发生故障、丢失、主要信息改变未到甲方备案的。

3.乙方提供的车辆信息为虚假信息的。 4.乙方无故不使用本人车辆超过5个工作日的。 5.乙方不服从甲方临时安排的。 6.乙方不服从所在部门（基层单位）统筹安排的。 （五）乙方因故当月未使用本人车辆在5个工作日以上的（不含5个工作日），甲方按实际使用天数发放油料补贴。 （六）乙方因在工作时间内驾驶本人车辆办理公务发生交通事故时，应及时向甲方安全监察部报案，由安全监察部协助处理。 由乙方进行事故处理并向参保保险公司索赔后，在规定范围内的超出部分费用凭有效凭据向甲方安全监察部申请，核实后，甲方按全责70%、主责75%、同责80%、次责85%、无责和意外100%的比例报销。（七）乙方车辆在工作时间内办理公务发生交通事故时，有以下情形之一的，甲方不承担事故费用的报销，由乙方自行负责1.当事驾驶人存在“酒驾”或“毒驾”。 2.当事驾驶人发生事故后逃逸或私撤现场的，或其他严重违法行为的。 3.若当事驾驶人非甲方安全监察部审核认定的人员的。 （八）乙方应自觉遵守国家《道理交通安全法》等有关法律法规，乙方及车辆若有违反国家有关法律法规行为的，其后果由乙方自行承担。 （九）甲方不承担乙方车辆任何原因的失窃、毁损等风险。 （十）乙方应遵守甲方制定的《工作用车管理办法》，并同意该办法为本协议附件。 五、协议终止及解除（一）如甲、乙双方在使用期届满时未达成延长使用期的协议，则该协议自动终止。 （二）协议期内，甲乙双方因各种原因，均可提前一周提出解除本协议。 （三）本协议期满后，若甲乙双方未提出异议，视为自动续签。

私车公用协议书

私车公用协议书 合同编号: 签订地点: 甲方:有限公司…………………………………………………(以下简称甲方) 乙方:(身份证号码:)……………………………(以下简称乙方) 乙方为甲方公司员工,鉴于乙方日常外出办事方便及业务繁忙时公司公车不能满足用车需要,乙方自愿将自己所属私家车一辆作为公司业务用车。为规范私车公用的相关事宜,明确甲、乙双方的责任及义务,经双方协商一致,达成协议如下: 一、使用范围: 有下列情况,均属于私车公用,适用于本规定: 1、乙方因公出差; 2、在本市接待甲方客户; 3、经部门负责人签批同意的本市办理其他因公业务。 二、车辆要求: 乙方所用私家车必须证照齐全、车况良好,投保交强险和其他相关保险。 三、使用方式: 1. 根据乙方所负责甲方的具体工作临时使用,但乙方需具备车辆驾驶资格,并由乙方自行驾驶,不另行配备司机。

2. 根据甲方需要,当因公需要使用乙方车辆时,乙方必须服从。 四、费用分摊: 1、需要私车公用的情况下,乙方出差填写《私车申请单》,过路费和停车费凭票实报实销,油费按照0.9元/km的标准进行报销。 2、乙方上下班路程上产生的费用(包括汽油费、停车费、过路过桥费等),相关费用由乙方自行承担。 3、私车公用期间,车辆的维护费、修理费、年检费、保险费、由于违章产生的罚金及相关费用等均由乙方自行承担。 4、根据油价涨跌,甲乙双方协商适时做出相应的调整。 注1:南通市区范围内私车公用的过路费、停车费也凭票实报实销。 五、风险承担: 1、签订本协议时,乙方必须提供驾驶证、车辆行驶证、保险卡等有效证件并留存复印件给甲方。 2、乙方在协议期内应严格遵守《中华人民共和国道路交通管理条例》及有关交通法律法规。如出现任何酒驾、违规、事故及肇事行为,乙方应承担由此产生的全部责任及损失,且甲方不承担在协议期间引发的第三者责任。 六、协议终止及解除: 1、如甲、乙双方在使用期届满时未达成延长使用协议的,则该协议自动终止。 2、因乙方车辆状况原因导致车辆无法正常行驶时,甲方有权解除协议。

关于私车公用的管理规定

关于公司私车公用的管理规定 第一章总则 第一条为加强私车公用管理，提高工作效率，增强企业凝聚力，制定本规定。 第二条本规定适用于所有公司私车公用的车辆。 第三条本规定所称私车公用，是指符合一定条件的人员报经公司总经理批准后将其私有车辆用于公务活动。 第二章条件及审批程序 第四条具备驾驶资格且符合以下条件之一的人员可申请私车公用； 1、对本公司有特殊贡献人员； 2、在本公司担任特殊职务人员； 3、确因公务所需经常使用车辆，但公司又不能满足需要的。 第五条私车用于公司业务前，必须事先提出申请，经公司总经理批准后（附私车公用申请表）方可。申请项目包括：申请人、申请时间、使用目的、使用时间、使用车辆种类和车辆、人身保险情况等。 第六条对于符合私车公用条件且已经总经理批准的，应与公司签订私车公用书面协议。第三章费用报销规定 1、每月可按区域享受区域油费补贴标准，凭发票额度内予以实报实销。 2、每月过路过桥费凭发票实报实销。 3、已享受上述第七条，在其工作所在地县市内出差，不再派用公车，也不再报销出租车票 或其他公交车票。 第八条每月报销费用一次，报销时间为每月15号。报销时应填写《私车公用费用报销汇总表》并附上相应发票后规定程序报销。 第四章法律责任及其他 第九条私车公用车辆必须向车辆所在地车管部门办理强制保险和任意保险，办理一切车辆保险所需支出由车主自负。 第十条因私车公用而发生的交通责任事故，公司不承担任何责任。与交通事故相关的其它费用（如事故处理费、车辆维修费等），由车主自理。 第五章附则 第十二条公司对私车公用的归口管理部门及费用报销的审核部门为人事行政部。 第十三条本暂行规定自年月日起试行。 ******有限公司 年月日

关于私车公用费用补贴原则及管理办法(试行)

关于私车公用费用补贴原则及管理办法（试行) 1、目的 随着公司业务发展，为提高办事效率，公司针对因公务临时外出或长期用车需要，员工使用私人车辆的情况，对私车公用的员工进行一定的费用补偿，特制定本规定。 2、适用范围 本制度适用于公司全体员工 3、责任 3.1财务办公室负责本制度的制定和修改。 3.2总经理负责本制度的审批。 3.3公司各部门负责本制度的执行、监督。 4、细则 4.1、私车公用的申请 4.1.1因公务外出应首先向行政申请使用公司的公共车辆，在公司公共车辆无法提供时，可申请私车公用。 4.1.2员工确因公务需要临时使用私车外出时，必须事先填写《私车公用申请及行驶记录表》。 4.2.3员工的私车公用申请和费用审核由总经理批准。 4.2、私车公用费用的报销程序： 4.2.1员工即时填写《私车公用申请及行驶记录表》→填写费用报销单（《私车公用申请及行驶记录表》为报销附件之一）→报行政部审核→报财务部对费用金额进行核算→报总经理批准后→到财务部报销。 5、私车公用费用报销项目、计算方式及标准 5..1私车公用费用补助标准明细：

6、关于私车公用的管理 6.1员工在执行公司指派任务并自愿使用私人产权车辆者为私车公用行为，员工在规定时间驾车上、下班的行为，不属于私车公用的情形。 6.2员工须及时填写《私车公用申请及行驶记录表》，经相关程序批准后方可外出。 6.3员工每次因公务外出，须按照《私车公用申请及行驶记录表》的内容及时地认真做好记录，不准弄虚作假欺瞒公司，否则不予报销相关费用。 6.4员工的私车公用车辆，须自行确保驾驶证、车辆行驶证、车辆保险（含第三责任险和驾乘险）等车辆管理及交管部门备查所需的证件及相关手续齐全并始终在有效期限内，否则由此产生的一切后果均由本人自行承担。 6.5私车公用驾驶员必须自觉遵守交通规则，服从交通部门的指挥和检查，维护交通秩序，文明驾车，确保行车安全。 6.6私车公用车辆的驾驶人员必须严格遵守车辆管理和交通法律法规，对于违反交通法律法规的相关处罚和造成的一切损失均由驾驶员本人承担。 总经理审批： 山东凯杰建筑工程有限公司 2

私车公用协议书范本

私车公用协议书范本 SANY GROUP system office room 【SANYUA16H-

私车公用协议书 甲方（公司）： 乙方（个人）： (车辆行驶证登记车主签字) 随着公司业务的发展和经营规模的扩大，对外经营工作和接待任务的地日益增加，交通工具在公司经营管理活动中的作用越来越明显。从提高办事效率、降低公司汽车维护成本、优化资源配置等方面考虑，经甲乙双方共同协商一致，特制定本协议： 一、车辆现状 车辆名称：车牌号：车架号： 车辆购置时间：年月日车辆状况：。 登记车主：（□乙方 / □非乙方）。 （若登记车主非乙方，需要提供： 1、关系说明文件：如夫妻，提供结婚证复印件一份；如家庭亲属，提供户口本复印件一份。 2、登记车主签字确认的“知晓并同意乙方私车公用行为，并同意与乙方共同承担该协议约定的义务。”的证明文件。） 二、甲方的权利义务 1、协议期内甲方享有该车辆的有效使用权。 2、甲方负责承担乙方在使用该车辆办理公务时，经核定合理发生的燃油费、过路费、存车费、协议期内年限发生的年检费及保险费用。此项补贴仅限于郑州市内，市外另行约定。 3、甲方除承担第二条第2款中涉及的相关费用外，不再承担任何由该车辆使用造成的费用及法律责任。 4、甲方对于该车辆除使用权外的其他物权纠纷一概不承担责任。 三、乙方的权利义务

1、乙方将该车辆用于公司事务使用时，享有第二条第2款中相应费用报销的权利。 2、乙方应提供驾驶证、车辆行驶证、保险单等有效证件并保证在协议期间的真实有效性以及车况的完好。 3、乙方在使用该车辆时应严格遵守交通规则和相关法律法规，谨慎安全驾驶并及时维护保养； 4、乙方在使用该车辆期间造成的任何侵权责任（含交通事故），均由乙方承担责任。 四、乙方应在签订本协议的同时，提供身份证复印件、驾照复印件和车辆行驶证复印件各一份，供甲方留存。 五、本协议签订前，乙方已完全理解本协议的全部内容，签订本协议是乙方的真实意思表示，乙方同意按本协议约定内容使用车辆。 六、本协议有效期年，自年月日至年月 日止。 七、协议的终止及解除 1、协议期间，因车辆状况或其他原因使车辆无法为甲方提供服务的，甲方有权单方解除协议；乙方更换服务车辆应另行签署协议，另行签署日起本协议自动终止。 2、如甲乙双方在使用期届满时未达成延长使用期的协议，则该协议自动终止。 3、乙方离职，此协议随同离职生效日终止。 4、协议期内，甲乙双方如有特殊情况需提前解除协议，需提前一周提出解除本协议。 八、本协议经双方签字或盖章后生效，若有其他未尽事宜，由双方另行协商解决。 九、本协议一式两份，甲乙双方各执一份。

南京xx集团xx中心私车公用管理制度(含全套表格及协议)

南京xx科技集团股份有限公司 xx中心私车公用管理制度 2018年5月23日修订第1版 Xx中心发布

目录 一、目的 (3) 二、适用范围 (3) 三、管理职责 (3) 四、申请条件及审批程序 (3) 五、报销标准 (4) 六、报销要求 (5) 七、车辆的管理 (5) 八、违章与事故处理 (5) 九、关于私车损失的赔偿 (5) 十、附则 (5) 附件一： (7) 附件二： (8) 附件三： (9) 附件四： (10)

一、目的 为满足公司外出业务的临时用车需求，提高外出工作效率，本着资源利用最大化的原则，根据公司《车辆管理制度》及其他相关规定，特制定本制度。 二、适用范围 本规定所称私车公用，是指符合一定条件的人员自愿申请，并报经公司领导层批准将其私有车辆用于公司公务的行为。适用于经公司审核、审批后确认符合条件的外联、外出工作人员和管理人员。 三、管理职责 （一）综合管理部 1.行政主管负责私车公用管理制度的拟定，并根据业务部门的意见进行修订。 2.行政主管负责私车公用协议的签订和备案。 3.行政主管负责私车公用的车辆资料的登记、审核及备案。 4.车队负责私车公用的出车安排及临时调度管理。 5.行政主管负责私车公用里程的计算、审核及相关费用的初审。 6.车队有责任为私车公用驾驶员提供相关路线指导及其他后勤保障等。 7.车队有责任及时统计公司现有业务车辆最新使用、调度情况，以便私车公用提请及审批。（二）财务部 1. 负责私车公用费用补贴的审核。 2. 负责相关费用的发票、收据等的审核。 3. 负责相关费用的补贴的发放及报销手续等。 （三）私车公用的执行、使用部门 1. 负责私车公用车辆的申请、登记、备案。 2. 负责私车公用的出车使用审批。 3. 负责私车公用外出工作需求、外出线路、行使里程及外出人员考勤的审核。 4. 负责对私车公用所产生的费用等进行核实、初审。 四、申请条件及审批程序 1、拥有其名下的私人汽车、汽车保险及登记手续齐备、驾龄超过3年且符合外联或外出作

私车公用协议书签字版本

私车公用协议书签字版本 Revised by BLUE on the afternoon of December 12,2020.

私车公用协议书甲方： 乙方： 鉴于乙方为甲方单位在职员工，为提高办事效率、降低公司汽车维护成本，甲方因业务需要安排乙方使用私有车辆办理公务经双方协商一致达成私车公用协议如下： 一、车辆现状 若登记车主非乙方，需提供： 1、关系证明：如夫妻，提供结婚证复印件；如家属亲属，提供户口本复印件。 2、登记车主签字确认的“知晓并同意乙方私车公用行为，并同意与乙方共同承担该协议约定的义务”的证明。 二、私车公用期限为乙方向甲方供职服务期限： 自年日至年月日止，以乙方实际供职期限为准。

三、乙方在使用该车辆时应严格遵守交通规则和相关法律法规，安全驾驶并及时维护保养。乙方应保证第三者责任险保额50万以上，因乙方原因造成第三者责任险免赔的，由乙方承担相应赔偿。 四、车辆使用由乙方自行安排,但乙方工作期间必须同时提供本协议所指定车辆为甲方服务，不得以车辆原因作为解释未完成工作任务的理由。 五、甲方承担一定限额的车辆燃油费用，燃油费用以外的其他任何费用及法律责任一律由乙方自行承担。 1、甲方负责开立（充值）指定车牌号的加油卡提供给乙方汽车加油使用。一车一卡、专卡专用的制度，不得转借。 2、乙方汽车除加油卡充值以外的任何费用及法律责任一切由乙方自行承担，包括但不限于车辆维修费用及交通事故责任。 六、协议终止及解除 1、协议到期自动终止。 2、因车辆状况或其他原因使车辆无法为甲方提供服务的，甲方有权单方解除协议；乙方更换服务车辆应另行签署协议，另行签署日起本协议自动终止。 3、乙方离职，此协议随同离职生效日终止 4、双方如有特殊情况需提前解除协议，需提前一周通知。

私车公用车辆租赁协议范本模板

编号： JT-20219071 甲 方：______________________________ 乙 方：______________________________ 日 期：_________年________月_______日 私车公用车辆租赁协议范本模板 The parties may dissolve the contract upon consensus through consultation.

[标签:titlecontent] 私车公用协议 甲方： 乙方： 甲方因单位业务需要，使用乙方（车牌）（私）汽车一辆，经双方协商一致，达成协议如下： 一、使用期限： 乙方自_201_年__1_月__1_日起，将车辆（）交付给甲方使用，至_201_年_12_月_31_日收回。 二、使用方式： 甲方使用乙方汽车期间，乙方不得再将该车作为私车使用。 三、费用分摊： （一）甲方承担对乙方汽车在业务范畴内进行使用所发生的一切费用，包括汽油费、过路费、过桥费、停车费、清洗费、正常保养（修）等日常费用。 （二）甲方承担对乙方汽车使用期间的投保费用，包括交强险、车辆损失险、盗抢险、自燃险、第三责任险。

四、风险承担： （一）甲方在使用期内，承担乙方汽车发生的交通事故、失窃、毁损等风险，以下情况除外： 1、乙方违反《中华人民共和国道路交通管理条例》驾驶汽车发生交通事故； 2、乙方故意捏造汽车失窃、制造汽车毁损情况的。 五、协议终止及解除： （一）如甲、乙双方在使用期届满时未达成延长使用期的协议，则该协议自动终止。 （二）因车辆状况原因导致车辆无法正常行驶时，甲方有权解除协议。 （三）双方如有特殊原因需提前解除协议，需提前两周告知对方。 六、其他： （一）本协议未尽事项由双方协商解决。 （二）本协议自甲、乙双方签字（盖章）后生效。本协议一式两份，由甲、乙双方各执一份，具有同等法律效力。 （三）有关协议的一切争议，双方经协商解决未能达到一致的，任何一方可向甲方方所在地的法院提出起诉。 甲方（签字盖章）乙方（签字盖章） 年月日年月日

XX公司私车公用协议

XX公司私车公用协议 私车公用协议 甲方：XXX 有限公司 乙方： 甲方因工作需要，为提高管理人员的工作效率，允许乙方将本人私车（车牌）_________________ 一辆用于甲方的公务活动，经双方协商 一致，达成协议如下： 一、使用期限： ____ 年 ___ 月_______ 日至 _____ 年_____ 月 ______ 日。 二、使用方式及租金： 本协议期间，车辆原则上仍由乙方本人保管使用，用于甲方的公务活动；甲方需临时安排时，乙方应服从临时安排。无租金。 三、私车公用规范 （一）乙方必须具备以下条件： 1.乙方依法获得驾驶证，且经甲方安全资格审查合格。 2.乙方提供车辆为乙方本人所有（以车辆登记证书记载为准），已使用年限未超过15 年，已办理交强险、第三者险（三者险按照不低于50 万元保额标准进行投保）、车损险、乘坐险、不计免赔险等安全保险项目。 3.乙方车辆须是合法手续完备、安全性能良好，能正常使用（以公司技术部审查结果为准）。 （二）乙方车辆由乙方自行保管，自行负责车辆的维修保养及年审等，保证车辆技术状况良好，保证车辆手续合法有效。乙方自行购买路桥年票，乙方自行购买各项保险。乙方车辆每年年审后需重新向甲方提交车辆登记证书、车辆行驶证、保险单等资料原件及复印件。 XX公司私车公用协议

（三）甲方按月给予 乙方定额油料补贴，具体为—元、月， 由甲方以油卡充值方式支付给乙方。 （四）乙方有下列情形之一的，甲方不再为乙方提供定额油料补贴： 1?乙方车辆使用年限超过15年的。 2 .乙方驾驶人和车辆主要信息未到甲方登记，或车辆发生故障、丢失、主要信息改变未到甲方备案的。 3?乙方提供的车辆信息为虚假信息的。 4.乙方无故不使用本人车辆超过5个工作日的。 5?乙方不服从甲方临时安排的。 6?乙方不服从所在部门（基层单位）统筹安排的。 （五）乙方因故当月未使用本人车辆在5个工作日以上的 （不含5个工作日），甲方按实际使用天数发放油料补贴。 （六）乙方因在工作时间内驾驶本人车辆办理公务发生交通 事故时，应及时向甲方安全监察部报案，由安全监察部协助处理。 由乙方进行事故处理并向参保保险公司索赔后，在规定范围内的 超出部分费用凭有效凭据向甲方安全监察部申请，核实后，甲方 按全责70%、主责75%、同责80%、次责85%、无责和意外100%的比例报销。 （七）乙 方车辆在工作时间内办理公务发生交通事故时，有以下情形之一的，甲方不承担事故费用的报销，由乙方自行负责： 1.当事驾驶人存在“酒驾”或“毒驾”。 2?当事驾驶人发生事故后逃逸或私撤现场的，或其他严重违 法行为的。 3.若当事驾驶人非甲方安全监察部审核认定的人员的。

公司员工私车公用协议

. 私车公用协议 甲方： 乙方：身份证号码： 乙方为公司员工，因办理甲方业务，需使用乙方汽车一辆（私）（车牌号：），经双方协商一致，达成协议如下： 一、协议期限及租金： 自年月日至年月日止，无租金。 二、车辆使用方式： 1. 使用方式：根据乙方所负责甲方的具体工作临时使用，但乙方需具备车辆驾驶资格，并由乙方自行驾驶，不另行配备司机。 2. 根据甲方需要，当因公需要使用乙方车辆时，乙方必须服从。 三、费用分摊： 1.甲方承担乙方汽车的汽油费、过路费、过桥费、停车费、维护费，不承担车辆的维修费用及违章罚款等。 2.只有经甲方负责人签字批准使用，并在批准使用期限内所发生的上述费用由甲方承担，甲方根据乙方提供的费用原始单据、发票支付上述费用。 四、风险承担： 乙方在租期内应严格遵守《中华人民共和国道路交通管理条例》及有关交通法律法规。如出现任何酒驾、违规、事故及肇事行为，乙方应承担由此产生的全部责任及损失，且甲方不承担租用车辆于租用期间引发的第三者责任。 五、协议终止及解除： 1. 如甲、乙双方在使用期届满时未达成延长使用期协议的，则该协议自动终止。 2. 因车辆状况原因导致车辆无法正常行驶时，甲方有权解除协议。 3. 租车期间，乙方应服从甲方管理，遵守甲方规章制度，服从车辆调配，如不服从甲方管理或出现违纪现象，甲方有权提前解除协议。 4. 乙方离职情况下，自乙方办理离职手续之日起本协议自动终止。 5. 双方如有特殊原因提前解除协议，需提前一周告知对方。 六、其他： 1. 有关费用报销及支付按公司财务管理制度执行，协议未尽事项由双方协商解决。 2. 本协议自甲、乙双方签字（盖章）后生效。本协议一式两份，由甲、乙双方各执一份，具有同等法律效力。 3. 有关协议的一切争议，双方经协商解决未能达到一致的，任何一方均可向当地法院提出起诉。 甲方（签字盖章）：乙方（签字盖章） 年月日年月日 精选编辑word