Patterns of Profitability and Privatization

First, we examine enterprise profitability in detail by categorizing enterprises from different regions into different groups on the basis of operating performance.

Second, we examine the changing ownership structure for the north-east as compared with the national trend. This shows the progress of privatization as well as extent of state ownership of enterprise assets across regions. The ownership factor is one of the most robust explanations for productivity gaps found in the regression analysis.

How to define profitability for Chinese industrial enterprises?

The primary objective of industrial enterprises is to produce output by effectively employing inputs such as capital, labor, and intermediate inputs. In this production process, enterprises create value added, which is defined here as:

VA = Y – M + VAT = Y – (MINPUT – FC) + VAT;

VA: value added;
Y: gross value of industrial output;
VAT: value added tax bill;
M: intermediate inputs excluding financial charges;
MINPUT: intermediate inputs including financial charges;
FC: financial charges, mainly interest payments.

The above equation presents value added from the production perspective. Value added is created by the joint efforts of participants of enterprises and from the distribution perspective can be divided into a number of income components.

VA = ATP + TAX + D + FC + W;

ATP: after-tax-profits as an income flow to owners;
TAX: tax as a revenue flow to the governments;
D: current depreciation as a flow to maintain owners’ equity value;
FC: financial charges as a payment for banking and financial services;
W: wages and other benefits as a payment for labor services.

We believe that the above presentation on the composition of value added provides a useful framework for measuring and analyzing the performance of the Chinese industrial enterprises since it traces each of the key components of value added in each enterprise.

Based on the above basic payment components of value added, we can derive a few commonly used accounting items summarizing the income-creating capacity of an enterprise:

Value Added: VA = ATP + TAX + D + FC + W;
Gross Profits: GP = VA – W = ATP + TAX + D + FC;
Gross Cash Flow: GCF = GP – FC = ATP + TAX + D;
Profits: P = GCF – D = ATP + TAX;
After-Tax-Profits: ATP = P – TAX = ATP.

It should be noted that the above five accounting items can take a positive, zero, or negative value. Their values indicate a firm's profitability. Based on the five payment or income components of value added, we can classify enterprises into eight profitability categories:

GFIN=[-4] –M-W-FC-D-TAX if VA <= 0;
GFIN=[-3] –W-FC-D-TAX if GP <= 0 AND VA > 0;
GFIN=[-2] –FC-D-TAX if GCF <= 0 AND GP > 0;
GFIN=[-1] –D-TAX if P <= 0 AND GCF > 0;
GFIN=[+1] –TAX if ATP <= 0 AND P > 0;
GFIN=[+2] if ATP > 0 AND NROTA <= 5%;
GFIN=[+3] if NROTA > 5% AND NROTA <= 15%;
GFIN=[+4] if NROTA > 15%.

In the above categorization, M, W, FC, D, and TAX represent the five payment components of value added. The negative sign before these symbols can be read as “cannot pay all of”. The underlying implication for the above grouping is explained below:

• Group [+4]: Enterprises in this group are highly profitable with their after-tax return on total assets (NROTA) higher than 15%.
• Group [+3]: Enterprises in this group are very profitable with their after-tax return on total assets (NROTA) greater than 5% but less than or equal to 15%.
• Group [+2]: Enterprises in this group are profitable with positive after-tax profits, but their after-tax return on total assets is less than 5%.
• Group [+1]: Enterprises in this group would make profits if they did not have to pay all taxes. They have negative after-tax profits (ATP=VA-W-FC-D-TAX) but positive profits (P=VA-W-FC-D). The term -T tells us that these enterprises are not able to pay all taxes (including profit and value added taxes) but can pay depreciation, financial charges, wages, and intermediate inputs. This group of enterprises is profitable before paying taxes. Although they make losses after paying taxes, they still create net positive value for the society and could survive in both the short and long run if their tax obligations are renegotiated.
• Group [-1]: Enterprises in this group would make profits if they did not have to pay all taxes and depreciation. They have negative profits (P=VA-W-FC-D) but a positive gross cash flow (GCF=VA-W-FC). The terms -D-T tell us that these enterprises are unable to pay all taxes and depreciation, but can pay all financial charges, wages, and intermediate inputs. This group of enterprises has no problem in meeting their variable or working capital costs of production and can survive in the short-run. However they are not profitable after paying current depreciation and may not be able to survive in the long-run, since their existing capital will be depleted rapidly.
• Group [-2]: Enterprises in this group would make profits if they did not have to pay all taxes, depreciation and financial charges. They have negative gross cash flow (GCF=VA-W-FC) but positive gross profits (GP=VA-W). The terms –FC-D-T tell us that these enterprises are unable to pay all taxes, depreciation, and financial charges but can pay wages and intermediate inputs. This group of enterprises is able to cover their variable or working capital costs of production related to labor and materials, but can pay only part of their financial charges and none of their current depreciation. They could survive in the short-run if their creditors tolerate their non-performing short-term debts. But they may have to be shut down in the long-run, since they cannot recover their fixed cost of capital.
• Group [-3]: Enterprises in this group would make profits if they did not have to pay all the taxes, depreciation, financial charges, and wages. They have negative gross profits (GP=VA-W) but positive value added (VA=Y-MINPUT). The terms -W-FC-D-T tell us that these enterprises are unable to pay all taxes, depreciation, financial charges and wages, but can pay for intermediate inputs. This group of enterprises could still create some positive value added but could only cover part of their labor costs. If the enterprises could cut their employment and improve labor productivity, they may survive in the short-run. If they are unable to cut their labor costs, they may have to be shut down even in the short-run. These enterprises cannot survive in the long run, since they cannot recover their fixed cost of capital.
• Group [-4]: Enterprises in this group would make profits if they did not have to pay all taxes, depreciation, financial charges, wages and intermediate inputs. They have negative value added (VA=Y-MINPUT). The terms -M-W-FC-D-T tell us that these enterprises cannot pay all taxes, depreciation, financial charges, wages and intermediate inputs. This group of enterprises creates zero or negative value added. They cannot survive without net subsidies and may have to be closed down as soon as possible.

The purpose of grouping enterprises into the above eight categories is to link enterprise profitability with fixed and variable costs. This categorization reveals the underlying economic viability of enterprise operations. Poor-performing enterprises may be able to survive financially in the short-run through financial manipulations and non-payment of their obligations. However this would only buy some time for the enterprises to implement real reform and restructuring measures, such as cutting employment, changing product lines, improving product quality and raising sales.

Is the profitability of firms in north-east PRC improving?

Table 2.1 [ PDF 373.2KB | 73 pages ]-2.5 [ PDF 373.2KB | 73 pages ] shows the number of firms in each of the eight profitability categories over 1995-2002 for each of the three north-east region provinces (Liaoning, Jilin, and Heilong Jiang) as well as for the entire national sample. Since the size of the firm can vary greatly within the sample, we should not read too much from the results in these tables in terms of their impact on the economy. However, as each loss-making enterprise presents a similar challenges to the policy-maker or shareholders in terms of restructuring, it is still useful to examine closely Table 2.1 [ PDF 373.2KB | 73 pages ]-2.5 [ PDF 373.2KB | 73 pages ]. Table 2.2 [ PDF 373.2KB | 73 pages ] shows the profitability pattern for the national sample while Table 2.3 [ PDF 373.2KB | 73 pages ], Table 2.4 [ PDF 373.2KB | 73 pages ], Table 2.5 [ PDF 373.2KB | 73 pages ] presents the profitability pattern for Liaoning, Jiling, and Heirongjiang separately. Table 2.1 [ PDF 373.2KB | 73 pages ] is a consolidation of Table 2.2 [ PDF 373.2KB | 73 pages ]-{2.4 [ PDF 373.2KB | 73 pages ] and is useful for comparing each province’s performance with the national average performance. The information provided here contrasts sharply with the frequently quoted performance indicator in PRC, the number of loss-making enterprises in a region. Here we show the number of enterprises in eight different profitability conditions. Both policy-makers and shareholders need to have different responses to firms in different categories. For example, firms in categories [-4] and [-3] need to be considered for bankruptcy, while firms in categories [-2] and [-1], and [+1] probably need to be considered for restructuring. On the other hand, the amount of firms in categories [ +2], [+3], [+4] indicates the health and competitiveness of a region’s enterprises.

For the national sample results in Table 2.2 [ PDF 373.2KB | 73 pages ], there is clear evidence that the number of enterprises in the worst groups [-4], [-3], and [-2] has been declining from 3.8%, 13.2%, and 9.5% in 1995 to 2.7%, 8.7%, and 3.1% in 2002 respectively. The number of enterprises in the best groups [+4] and [+3] has been increasing from 19.4% and 9.7% in 1995 to 24.1% and 21.5% in 2002, respectively. As we show later, this improvement in performance is accompanied with the disappearance of many state-owned enterprises from our sample due to privatization and bankruptcy.

Similar patterns of improving performance can be observed for all the three provinces in the north-east region as shown in Table 2.3 [ PDF 373.2KB | 73 pages ], Table 2.4 [ PDF 373.2KB | 73 pages ], and Table 2.5 [ PDF 373.2KB | 73 pages ]:

• For Liaoning, the number of enterprises in the worst groups [-4], [-3], and [-2] have declined from 9.6%, 22.1%, and 11.8% in 1995 to 3.0%, 9.9%, and 4.1% in 2002 respectively. The number of enterprises in the best groups [+3] and [+4] have increased from 10.0% and 4.8% in 1995 to 22.0% and 16.2% in 2002 respectively.
• For Jiling, the number of enterprises in the worst groups [-4], [-3], and [-2] have declined from 10.0%, 20.2%, and 12.1% in 1995 to 2.8%, 14.0%, and 5.1% in 2002 respectively. The number of enterprises in the best groups [+3] and [+4] have increased from 11.9% and 5.6% in 1995 to 17.9% and 19.3% in 2002 respectively.
• For Heilongjiang, the number of enterprises in the worst groups [-4], [-3], and [-2] have declined from 6.6%, 17.7%, and 11.1% in 1995 to 2.3%, 13.8%, and 5.8% in 2002 respectively. The number of enterprises in the best groups [+3] and [+4] have increased from 13.2% and 4.9% in 1995 to 19.1% and 10.9% in 2002 respectively.

The above evidence provides a fresh insight into the economic conditions of the north-east. Unlike the popular view of poor performance, the region is actually improving at a similar pace as the rest of the country in the profitability of large and medium industrial enterprises, although it is true that the north-east still lags behind the national average in enterprise profitability. The details of the gaps are shown in Table 2.1.

Is capital moving from worst to best-performing firms in the north-east of PRC?

Another way to examine the performance of the north-east region is to look at the pattern of resource allocation involving capital and labor. In particular, the relevant policy question is whether capital is flowing from less efficient enterprises to more efficient ones. Using the eight profitability categories defined in the paper, Table 2.6 [ PDF 373.2KB | 73 pages ]-Table 2.10 [ PDF 373.2KB | 73 pages ] shows the amount of total assets what were being allocated to each of the eight categories of enterprises over the period of 1995-2002. The tables help us to understand how PRC’s capital market was functioning in an imperfect and fragmented institutional setting. The impression from reading newspapers and research reports is that PRC’s capital market is hugely distorted with repeated scandals and problems. But the careful examination of the national and regional samples shows a sharp contrast. One the whole, the well-performing groups of firms are getting more and more capital, while the poor performing groups are getting less.

• For the national sample, Table 2.7 [ PDF 373.2KB | 73 pages ] shows that the worst performing three groups reduced total assets only slightly from RMB879 billion in 1995 to RMB858 billion in 2002 but the best performing two groups increased total assets drastically from RMB1.7 trillion in 1995 to RMB4.441 trillion, an increase of 160%.
• For the Liaoning sample, Table 2.8 [ PDF 373.2KB | 73 pages ] shows that the worst performing three groups reduced total assets from RMB106 billion in 1995 to RMB46 billion in 2002, while the best performing two groups increased total assets drastically from RMB70 billion in 1995 to RMB195 billion in 2002, an increase of 179%.
• For the Jilin sample, Table 2.9 [ PDF 373.2KB | 73 pages ] shows that the worst performing three groups reduced total assets from RMB38 billion in 1995 to RMB27 billion in 2002, while the best performing two groups increased total assets drastically from RMB54 billion in 1995 to RMB133 billion in 2002, an increase of 146%.
• For the Heilongjiang sample, Table 2.10 [ PDF 373.2KB | 73 pages ] shows that the worst performing three groups reduced total assets from RMB50 billion in 1995 to RMB45 billion in 2002, while the best performing two groups increased its total assets drastically from RMB80 billion in 1995 to RMB161 billion in 2002, an increase of 101%.

Hence, on the whole, the north-east region is following the national trend in improving its allocation of capital. In particular, when we compare Heilongjiang with other regions in the best performing group, we find out that Heilongjiang has almost one quarter of its total assets in the most profitable enterprises and its best performing group’s share of total assets increased from 20.6% to 27.2%. This is largely due to the concentration of PRC’s petroleum enterprises in Heilongjiang. The consolidated Table 2.6 [ PDF 373.2KB | 73 pages ] provides a detailed comparison of each province’s capital allocation pattern with the national pattern and should be useful to local policy makers for assessing the performance and potential of their local enterprises.

Which groups of firms are cutting/creating employment in the north-east of PRC?

Is the improving performance of the north-eastern large and industrial enterprises helping employment in the region? A simple answer is no. On the whole, the sector of large and medium-sized industrial enterprises nation-wide has been cutting employment aggressively, especially in the north-east region, as shown in Table 2.11 [ PDF 373.2KB | 73 pages ]-2.15 [ PDF 373.2KB | 73 pages ].

• For the nation, the total employment for this sector fell from 38.226 million in 1995 to 26.419 million in 2002, a drop of 30.8%.
• For Liaoning, the total employment for this sector fell from 3.181 million in 1995 to 1.453 million in 2002, a drop of 54.3%.
• For Jiling, the total employment for this sector fell from 1.384 million in 1995 to 0.766 million in 2002, a drop of 44.6%.
• For Heilongjiang, the total employment for this sector fell from 2.299 million in 1995 to 1.196 million in 2002, a drop of 47.9%.

However, consistent with the improving overall enterprise performance in the north-east region, the well performing firms are expanding their share of employment at the expense of the poor-performing ones:

• For Liaoning, the share of employment in the worst-performing groups [-4], [-3], and [- 2] have declined from 5.3%, 19.0%, and 10.5% in 1995 to 1.4%, 7.2%, and 4.3% in 2002 respectively. The share of employment in the best-performing groups [+3] and [+4] have increased from 6.5% and 6.1% in 1995 to 21.2% and 7.2% in 2002 respectively.
• For Jiling, the share of employment in the worst-performing groups [-4], [-3], and [-2] have declined from 5.8%, 25.7%, and 7.7% in 1995 to 2.1%, 14.0%, and 3.7% in 2002 respectively. The share of employment in the best-performing groups [+3] and [+4] have increased from 20.6% and 2.3% in 1995 to 32.4% and 8.7% in 2002 respectively.
• For Heilongjiang, the share of employment in the worst-performing groups [-4], [-3], and [-2] have declined from 30.2% in 1995 to 19.8% in 2002. The share of employment in the best-performing groups [+3] and [+4] have increased from 21.9% in 1995 to 27.5% in 2002.

Hence, the improving enterprise performance in the north-east clearly improves the efficiency of the allocation of labor. The outcome of the labor market in the north-east region is entirely consistent with the pattern found at the national level. Again, this contrasts sharply with the general impression that the flexibility of the labor market in the north-east lags greatly behind the nation average. In fact, the extent of the cut in employment in the north-east region is much higher than the national average.

Is the privatization of SOEs slower in the north-east of PRC?

In the previous sub-sections, we have shown evidence from various angles on the improving performance of enterprises , including those in the north-east region. We argue that this improvement is primarily driven by market-oriented reforms, including particularly the privatization of SOEs. There has been a popular view that the north-east is much slower in privatization and that is one of the key reason for its overall lagging performance. This popular view is mis-leading, however. While the north-east region may have many more SOEs, the speed of privatization appears similar to that in the rest of PRC. We measure privatization by changes in the share of SOEs in the number of enterprises (Table 2.16 [ PDF 373.2KB | 73 pages ]-2.20 [ PDF 373.2KB | 73 pages ]), in total assets (Table 2.21 [ PDF 373.2KB | 73 pages ]-2.25 [ PDF 373.2KB | 73 pages ]), and in the total employment (Table 2.26 [ PDF 373.2KB | 73 pages ]-2.30 [ PDF 373.2KB | 73 pages ]) for each of the three north-east provinces and for the nation as whole. The results can be summarized as follows:

Number of SOEs

• For the nation as a whole, the number of SOEs fell from 15,361 in 1995 to 7,215 in 2002, a drop of 53% over eight years. The share of SOEs in the total number of firms in the sample decreased from 68.1% in 1995 to 32.5% in 2002, a decrease of 35.6 percentage points.
• For Liaoning, the number of SOEs fell from 1047 in 1995 to 257 in 2002, a drop of 75.5% over eight years. The share of SOEs in the total number of firms in the sample decreased from 67.5% in 1995 to 30.4% in 2002, a decrease of 37.1 percentage points.
• For Jilin, the number of SOEs fell from 531 in 1995 to 224 in 2002, a drop of 57.8% over eight years. The share of SOEs in the total number of firms in the sample decreased from 84.4% in 1995 to 52.1% in 2002, a decrease of 32 percentage points.
• For Heilongjiang, the number of SOEs fell from 608 in 1995 to 264 in 2002, a drop of 56.6% over eight years. The share of SOEs in the total number of firms in the sample decreased from 83.5% in 1995 to 51.4% in 2002, a decrease of 32.1 percentage points.

In summary, the three provinces in the north-east region privatized a higher percentage of SOEs than the rest of the nation and the share of SOEs in the total number of sample firms fell more than 30 percentage points over 1995-2002, consistent with the national trend.

Total assets:

• For the nation as a whole, the total assets in SOEs increased slightly from RMB3.888 trillion in 1995 to RMB5.085 trillion in 1999, and then fell to RMB4.51 trillion in 2002. The share of SOEs in total assets fell from 75.4% in 1995 to 45.6% in 2002, a drop of 29.8 percentage points.
• For Liaoning, the total assets in SOEs increased slightly from RMB361 billion in 1995 to RMB426 billion in 1998, and then fell to RMB291 billion in 2002. The share of SOEs in total assets fell from 82.6% in 1995 to 47.5% in 2002, a drop of 35.1 percentage points.
• For Jilins, the total assets in SOEs increased slightly from RMB148 billion in 1995 to RMB195 billion in 1999, and then fell to RMB158 billion in 2002. The share of SOEs in total assets fell from 87.6% in 1995 to 58.3% in 2002, a drop of 29.3 percentage points.
• For Heilongjiang, the total assets in SOEs increased slightly from RMB197 billion in 1995 to RMB233 billion in 1999, and then fell to RMB171 billion in 2002. The share of SOEs in total assets fell from 88.3% in 1995 to 47.1% in 2002, a drop of 41.2 percentage points.

In summary, in the north-east region, the level of total assets of SOEs either fell or grew only slightly, but the share of SOEs in total assets fell significantly, ranging from about 30 percentage points in Jilin, which is the national average, to 35 percentage points in Liaoning and 41 percentage points in Heilongjiang. Hence, arguably the privatization of SOE assets in the north-east during 1995-2002 is more aggressive than the national trend.

Employment

• For the national sample, the employment by SOEs fell from 31.337 million in 1995 to 13.072 million in 2002, a cut of 18.265 million or a decrease of 58.3%. The share of employment by SOEs in the sample fell from 82.0% in 1995 to 49.5% in 2002, a drop of 32.5 percentage points.
• For Liaoning sample, the employment by SOEs fell from 2.687 million in 1995 to 0.774 million in 2002, a cut of 1.913 million or a decrease of 71.2%. The share of employment by SOEs in the sample fell from 84.5% in 1995 to 53.2% in 2002, a drop of 31.3 percentage points.
• For Jilin sample, the employment by SOEs fell from 1.252 million in 1995 to 0.532 million in 2002, a cut of 0.72 million or a decrease of 57.5%. The share of employment by SOEs in the sample fell from 90.5% in 1995 to 69.4% in 2002, a drop of 21.1 percentage points.
• For Heilongjiang sample, the employment by SOEs fell from 2.137 million in 1995 to 0.811 million in 2002, a cut of 1.326 million or a decrease of 62%. The share of employment by SOEs in the sample fell from 92.9% in 1995 to 67.8% in 2002, a drop of 25.1 percentage points.

In summary, the fall in employment by SOEs in the north-east sample is not less than in the national sample, although the percentage drop in the share of SOE employment in the north-east sample is smaller than in the national sample. But still the privatization of SOE employment is very impressive.

All the above measures of privatization in terms of number of SOEs, their total assets, and their employment show that PRC’s privatization program in the north-east region is as aggressive as the national trend, if not more aggressive. It is true however that the north-east region was much more dominated by the SOEs than the rest of PRC at the beginning of the reform. Also, many partially privatized enterprises are still with a significant share of state ownership. We should also remember that our sample covers the entire large and medium-sized industrial enterprises sector in PRC, so enterprises that become smaller and no longer qualify for the group exit from our sample every year.

The results in this section show clearly that the performance of the large and mediumsized industrial enterprises in the north-east region in terms of detailed profitability has been improving significantly, consistent with the national trend. Also the privatization of SOEs in the north-east region is as aggressive as in the rest of PRC. These conclusions contrast sharply with the general impression that the north-east region is far behind the nation in reform and in the development of the industrial sector during the reform period leading to large gaps in performance between the north-east region and the rest of PRC. In order to resolve the seeming contradictory evidence, we need to define clearly performance indicators and use regression analysis to explain the gaps in performance between the north-east and other regions. This is the task of the next section.

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