- Email: [email protected]
A structural analysis of the inventory behavior of Hungarian industry
27
Engineering Costs and Produclion Economics, I5 (I 988) 27-34 Elsevier Science Publishers B.V., Amsterdam - Printed in Hungary
A STRUCTURAL
ANALYSIS OF THE INVENTORY OF HUNGARIAN INDUSTRY
BEHAWOR
Attila Chikan Karl Marx University
of Economics,
I INTRODUCTION
Recent investigations have explored in detail the characteristics of macroeconomic inventory formation in Hungary [in English, see Abel (1984), Abel and Ricke (1981), Abel and Kiiriisi (1986), Chikan (1981, 1984, 1986), Csikos-Nagy (1981), Fabri (1981, 1986), Hunyadi and Psenak (1986), Nagy (1981), Riecke (1984), Tiimpe (1986)], these analyses discovered that behind the aggregate inventory data there is a rather special and definite structure which must be disclosed if we want to give a really relevant explanation of inventory phenomena, The study report of Matits and Temesi (1985) has thrown a special light on the need for such an analysis. An extended research has started* a few months ago aiming to give a microeconomic basis for exploring the reasons and structure of aggregate inventory behavior (with special reference to the inventory cycle). This paper is intended to give a summary of the results according to one special aspect used in the first phase of the research.
II OBJECTIVES AND METHODS OF RESEARCH II.1 Objectives
The main questions which we plan to investigate are the following: * I’m indebted to I&v&n Abel and ViktSa
Dalkb for their
many suggestions and other extremely valuable assistance. The computatioR~ work has been carried out by L&s&5 Csexj&s, whd also deserves special thanks.
Budapest. Hungary
(i) How can the inventory behavior of companies be characterized in time and structure? (ii) Which are the main microecooomic influencing factors of company inventory behavior? (iii) What connections can be found between inventory formation on the macro and micro levels? (iv) How do the basic marcoeconomic processes influence company inventory behavior? (i) How can the central (government) regulation influence the inventory behavior of companies and what kinds of feedback are there?
II.2 Methods employed
The research is to be carried out by using three basic approaches: -
-
statistical analysis case studies interviews
This paper is restricted to discussing part of the results of the statistical analysis. The two other methods--case studies and interviews-are for both checking and the results of the statistical approach. Detailed case studies of nineteen companies have been written by managers, discussing the inventory formation of their companies from 1968 to 1984 and giving the reasons for the various changes. Over twenty interviews with top managers and leading economists working for government organizations have been carried out and more are planned to explore the nume~~lly non-expressible facts and inte~lations.
28 11.3The statistical data base The data base we use is the data bank of the annual balance data of all Hungarian companies, available since 197 1. This is an extremely wide and valuable data set, the use of which, however, requires special attention first of all because of its bulk. The first step of the statistical work was to designate those data which should be used in the analysis. we have restricted our research to First, industry-all other sectors (agriculture, trade, etc.) have been left out. This step was justified by’two aspects: (i) We wanted to keep the analysis within limits which we thought we can handle. (ii) The share of industry from the total inventory stock is over one third, so it is definitely the most important sector which determines much of the factors influencing inventories in other sectors. Based on our preliminary considerations 39 original variables and 52 derived variables (indeces) have been chosen for the analysis. Since the number of industrial companies is fluctuating at about 1100 each year, we have a three dimensional block of data of the size 1100 x 91 x 14. III THE STRUCTURE OF INVENTORY STOCK AND INVENTORY INVESTMENT After carrying out many elementary statistical operations we decided to first explore the structure of annual inventory investment and of inventory stocks. This paper provides the result of this analysis. For the investigation we have decided on selecting some basic aspects which can be measured using our data base. So we characterized each company in each year with a twelve element vector, each element of which expresses and measures one of our characterizing aspects. The following aspects have been considered (the definitions are detailed in Chapter 111.2): 1 ownership: state companies vs. cooperatives 2 type of industry: extracting (mining) vs. manufacturing industry
3 branch of industry (based on the Hungarian statistical system) 4 size of company (characterization by number of employees and total sales) 5 market orientation (selling on internal, and/or COMECON and/or Western markets) 6 market share (proportion of sales from the total sales of sub-branch) 7 growth rate (this and all further characterizations are based on the relation to the industrial average) 8 redistribution rativthe effect of taxes and subsidies paid and received 9 profitability: annual profit per invested capital 10 inventory turnover 11 inventory investment ratio (annual inventory investment/initial inventory) 12 inventory structure (the ratio of input inventories, work-in process (WIP) and output inventories). An analysis of the data structure above aspects will be carried “sample” years. As a first step compared the data for the last two period examined, 1983 and 1984.
according to the out for several we studied and years of the time
III. 1 General conclusions from the structural analysis Three important general consequences can drawn from these first steps of the analysis:
be
1 The structure of the wole sample is extremely stable from two important points of view. (i) The distribution of both the inventory stocks and inventory investments. We have drawn about 600 histograms of inventory stocks and about 300 of inventory investments, in very different groupings and there could hardly be found any other distribution than the following patterns:
29 The most striking experience was to see that while there has been a permanent and high inventory buildup in Hungarian industry during the period examined, in each year and each group almost half of the companies actually decreased their inventories. This fact was unexpected by all experts when first discovered. The histogram of inventory stocks shows the concentration of inventories: a few companies hold the majority of stocks, again considering each category. (ii) The structure of inventory stocks by stage of manufacturing has been the other very stable element of all investigations. It has been long known that the industry as a whole has a structure of inventories (7l-72% input, l7-18% WIP, I l-12% output inventories) which does not change in time. But it was not clear that this is valid almost also at company level-at least in our analysis we had a rather similar structure in almost all cases. This structure is a consequence of market conditions in Hungary (namely, the general overdemand in the vast ma,ority of sub-markets). We all know the importance of its effects-but it was inseresting to see how strongly it influences the whole inventory system. 2 In most analyses one could easily follow and explain the behavior of input and WIP inventories and their changes. However, output inventories in most cases showed very irregular, sometimes even chaotic behavior. This is a warning that even though output inventories have the smallest share of the total, their behavior can be a very important signal of economic events. 3 There are some aspects of the analysis (or, on the other hand, some groupings) in which case the relative standard deviation is small-while in some other cases there are only a few companies around the average. In the first case one can define a company which is in some respects “typical”: in the second case it would be a mistake, since no or only a few actual companies can be ordered to the average. This fact is very important in Hungary where the central government tries to influence the inventory behavior of the companies with financial regulators the values (ranges, etc.) of which are calculated on an “average” basis. Quite naturally, the effect of
such a regulator
will be completely
different in a case
when it is influencing an aspect where there are many “average” companies compared to the other case, when there are no such companies. Here we just mention that those large companies which mostly influence the overall inventory situation in Hungarian industry can hardly be regulated by such general
rules anyway.
III. 2 Characteristics of the data set by the twelve aspects In the following, we detailes of the analysis we can use the above shall follow these step I Ownership:
shall give the most important carried out. As a framework twelve aspects and thus we by step.
state companies
vs. cooperatives
From the total number of companies (I 148) there were 541 state owned (47. I %) and 607 cooperative (52.9%) companies in 1983. The proportion of the companies in the two groups did not change during the 1971-84 period. The main conclusion is that from our point of view it is enough to analyse the state companies for two main reasons: - The share of the state companies from the total inventory stock is over 80%, which means that their behaviour has a decisive impact on the inventory cycle; - the structure of inventory stock and inventory investment in the years examined (1971, 1977, 1983, 1984) is so close to each other that the data of cooperative companies can be roughly considered a scaled-down equivalent of the data of state companies. From now on all statements refer to state companies only. 2 Type of industry: extracting vs. manufacturing industry
(mining)
The vast majority of companies belong to the manufacturing industry (over 900/,). The average size of companies is much larger in the first group, consequently inventory stocks are higher as well.
30 The structure of inventory investments is entirely different for the two groups in a given year, so this aspect of grouping seems to be relevant when examining inventory behavior.
TABLE
1
Inventory stock in the average the end of 1984
companies
Total state-owned industry
branches
Without
largest
inventory
holders
at
(20% of all
3 Branch of industry According to the Hungarian statistical system, the following eight branches are considered: 1 mining and drilling 2 electrical energy production 3 metallurgy 4 machine (engineering) industry 5 building material industry 6 chemical industry 7 light (textile, leather, wood etc.) industry 8 other industries. The structure of inventory investments is different in the various branches by stage of manufacturing (i.e. input, work-in-process, output inventories) and from year to year. These differences are smoothed out over the years; this isshown by the rather stable structure of inventory stocks. The ratio of inventories by stage of manufacturing can be considered as a kind of “norm” or “standard” characteristic of the given branch. In examining the macro cycles, inventory investment by branches is an important factor-partly because of the above statistical facts and partly because government control is to a great extent practiced by branches-and this control has an extremely important influence on inventory behaviour. An interesting discovery was that if the top 20% of the companies, i.e., the biggest ones are left out of the analysis, the average inventory levels tend to be very even (Table 1). This fact is very important given that government regulations (mainly financial) generally aim at the “average” companies. Our results show that this type of control can be justified from this point of view only provided that the different treatment of the large companies can be ensured. However, it can be easily seen that this way only a relatively small proportion of the total stock (28.8%) can be controlled. So this regulation can be efficient to some extent from the point of view of smooth operation
in various
companies)
Industry
Total
Average
No. of
Average
No. of
inventory
com-
inventory
com-
stock
panies
stock
panies
(mFt)
left out
(mFt)
Mining
25
463
11
188
Electricity
22
371
2
254
Metallurgy Machine
24
954
12
150
172
492
50
163
39
223
116
Building materials
58
615
22
147
Light
164
200
12
127
Other
37
2s
0
25
Total
541
Chemical
205,349
112
59,095
(with the condition mentioned), but not in controlling total inventory investment in industry. This is one of the failures of our government control system. 4 Size of companies The definition of the “size” of a company can be very different. The following classification was used: Large companies: - number of employees exceeds 15,000 persons, or - total sales exceed 4 billion Forints. Small companies:. - number of employees is less than 500 persons, or - total sales are less than 0.5 billion Forints. companies: Those for which none of the above criteria hold. According to this classification we have 385 small, 87 average and 74 large companies. Average
31 The F-tests show that this is an extremely s@nificant classification. This is one of the few groups, where even the histograms of inventory stocks (by stage of manufacturing and by years) are different. The distributions of small companies show the regular pattern, while those of the average and large companies are relatively even. (The histograms of inventory investment show the “regular” pattern). It is interesting that the total inventory investments in both years are strongly correlated (rb0.8) with the investments in input stocks in case of the large companies, with the investments in output stocks at the small companies, while at the average companies the correiation of total inventory investment was high with the input stock investment in one year and with the work-in-progress in the other year.
TABLE 2 Average inventory stock and investment in the various groups according to market orientation Million forints 1984
1983
Market
Inventory stock
Inventory invest_ ment
Inventory
Inventory investstock
ment
Internal sales only
125
9
128
10
COMECON export
111
12
208
11
Western export
221
25
246
32
Export in both relations
581
100
589
106
5 Market orienfurion In this respect we have ~sting~sh~ four groups of companies - sales only in the internal market - export only within COMECON countries (besides domestic sales) - export only to Western countries - export to both West and COMECON. In the various groups one finds 179, 27, 77, and 258 companies, respectively. This proved to be again a very important classification. Both the inventory stock and the inventor investment at the average companies is penally the same within one group for the different years, while there is a large difference among the groups (Table 2). This is, of course, in close connection with the fact that export orientation is more common in the case of large companies. The difference in the structure of inventory stocks between the two large groups is striking. Those companies which sell only on the domestic market practically hold no output stocks, and their work-inprogress is also minimal, Both types of stocks are considerably higher at the exporters (Table 3). This is a direct consequenoe of the different delivery requirements of the domestic and the export markets.
6 Market share This factor has been measured with the proportion of the sales of a particular company from the total sales of its sub-branch of industry. The groups have been formed on the basis of this proportion being less than l/16; l/8; l/4; l/2; and greater than l/2.
TABLE 3 Inventory structure of companies of different market ovation Market orientation
Input stock %
Work-inQrogrws %
Output stock %
Companies selling on domestic market only
88.9
6.9
4.2
Exports
71.3
17.3
11.4
Examinations show that this classification is again in very close connection with company size. However, there is a great difference among the various groups in their structure of inventory investments, much larger than in case of the grouping by company size. The reason is yet to be explored.
32 7
Growthrate
The growth rate of the individual companies is measured in their relationship to the industry average. Namely, the following four categories have been applied : decreasing: growth rate 0 small: growth rate less than Z/3 industry average medium: growth rate between Z/3 and 4/3 average large: growth rate over 4/3 average It should be noted here that the same criteria have been applied for all the remaining aspects (8-12, without the 0 group at 10 and 12). The main observation is that companies experiencing different growth rates have basically the same level and structure of inventories+even though the status of a particular company is very transient from year to year. So this grouping is not significant for the whole sample but can be very significant for a particular company. The basic characteristic of this grouping is somewhat similar to the classification by branches from the point of view that there are great differences in annual inventory investments which are smoothed out over the years resulting in an even inventory level. 8 Redistribution
ratio
By “redistribution” here the net effect of state taxation and support is meant. If X’ denotes the profit of a company before taxes and receiving any subsidies and X, denotes the profit on the actual balance sheet, the following measure of redistribution (r) can be defined:
groups will have very similar distribution patterns both by years and by types of inventories. It is interesting that the companies in the smallest redistribution group hold the largest output inventories by far and their average is 4-5 times greater than that of the whole sample! (One straightforward explanation, which still must be checked: these are the companies which are left to themselves by the state, which forces greater market adaptibility on them, which makes higher output inventory a necessity.) 9 Profitability Profitability is measured by the ratio of profit (after redistribution) and total invested capital. It is a very important observation that this grouping is* investment are influenced by protitability in the case of Hungarian companies. The second interesting result is that the average inventory stock is higher in the groups of negative and low profitability. The structure of inventory is quite different in the companies showing a deficit than in any of the other groups (Table 4). 10 inventory
turnover
This was measured by the ratio of total inventories to total sales. This ratio is small when the turnover is high. TABLE 4 Average inventory stocks and their structure in groups according to provability Year: 1984
X,-X,
Groups
r = cx, + X,)/2
The effect of the level of redistribution on the general behavior and operation of the companies is tremendeous and we wanted to see its relation to inventory behavior. The most important observation is that redist~bution changes widely from year to year. A particular company can shift from the highest to the lowest group in one year. It is not really surprising that if the largest companies are left out, the four
Distribution
Average inventories
by stage
of manufacturing
(%)
(mW
Input
WIP
output
Deficit
402
65.4
21.9
6.7
Low profitability
412
73.5
16.5
10.0
profitability
373
75.0
15.3
9.7
High profi~bility
334
69.7
14.4
15.9
Average
l
Not
inventory.
significant:
neither
the
inventory
level
nor
the
33 The order of the various groups is the same for both years examined and for all types of inventories: higher turnover rate means lower absolute level of inventories. This is not absolute, but reflects the regular and stable structure of the inventories in Hungarian industry (Table 5). It can also be seen that companies with a low turnover hold high output inventories at the expense of input inventories. TABLE
5
Inventories
The internal structure of inventories is completely different in the two years examined, which definitely shows that a large number of companies go from one group to another each year (since the structure of inventories of a particular company normally does not change too much from year to year). This is one of the rare cases when not all the histograms are “regular” ones. For example, in both years almost all companies which decreased total inventories (group 1) decreased their intput inventories as well (while their WIP and output inventories show the regular pattern).
in groups according to inventory turnover
Year: 1983
12 inventory strwtwe Type of inventory
Inventory turnover
High Average
WIP
Input
Total
output
mFt
%
mFt
%
mFt
%
mFt
176
72.1
38
15.6
29
11.9
244
266
75.1
56
15.8
31
8.8
354
330
68.2
70
14.4
83
17.1
484
In almost all groupings we found that they are significant for the inventory investment (even in those cases when not significant for inventory stock); this classification is an exception, which is rather surprising. I1 Inventory investment ratio This was measured by the ratio of inventory investment in a particular year to the initial inventory of that year. It is interesting that in the group of “average” inventory investment there are only very few companies in both years examined (e.g., in 1983, the number of companies in the negative, small, average and high groups were 194,53,26,268, respectively) and this is all the more so, since we know that the distribution of companies by inventory investment is rather concentrated. This means that the average has a very high standard deviation and that inventory investment is not correlated with the initial inventories, which is in fact the case for all groups except, not surprisingly. in the case of the group of average ratio.
The internal structure of inventories was measured by the ratio of input inventories to the total inventories. We used three categories (low, average, high) based on the usual criteria. The groups have an extremely interesting structure: in the group of high input inventory proportion the WIP inventories are very low, compensating the high input inventories to the lefel that the output inventories have the same ratio. The average inventory is much lower in the group of low input inventory ratio, while practically the same in the two other groups (in 1984: 256, 453, 441 mFt, respectively). Inventory investments in the two years examined happened in a very different structure-in general, almost all structures of this classification are rather mixed, with less regularity than in most other cases. IV CONCLUSION
The structural analysis reported here is only the very first step of an extended study. However, it has already provided (i) some important starting points for further analysis (ii) a fevi conclusions of interest for economic policy makers. The main general issues derived from the analysis are given in Chapter III. 1. The detailes given in 111.2.(i) prove that the set of the twelve characterizing aspects was well selected since significant conclusions can be drawn by their application (ii) provided good points for further statistical analysis when more sophisticated methods will be used.
34 REFERENCES
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Abel, I.: Determinants
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Model of Hungarian Abel, I. and Riecke, Behavior
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Chikan
Economy,
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in ChikPn Chikln,
Disequilibrium
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Inventory
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Sector,
and the Volume of Stocks, in (Cycles?)
the Proceedings Springer-Verlag, A.,
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1923,
in the Hungarian
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Influencing in Chikln
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Budapest,
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Kiado,
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Engineering Costs and Produclion Economics, I5 (I 988) 27-34 Elsevier Science Publishers B.V., Amsterdam - Printed in Hungary
A STRUCTURAL
ANALYSIS OF THE INVENTORY OF HUNGARIAN INDUSTRY
BEHAWOR
Attila Chikan Karl Marx University
of Economics,
I INTRODUCTION
Recent investigations have explored in detail the characteristics of macroeconomic inventory formation in Hungary [in English, see Abel (1984), Abel and Ricke (1981), Abel and Kiiriisi (1986), Chikan (1981, 1984, 1986), Csikos-Nagy (1981), Fabri (1981, 1986), Hunyadi and Psenak (1986), Nagy (1981), Riecke (1984), Tiimpe (1986)], these analyses discovered that behind the aggregate inventory data there is a rather special and definite structure which must be disclosed if we want to give a really relevant explanation of inventory phenomena, The study report of Matits and Temesi (1985) has thrown a special light on the need for such an analysis. An extended research has started* a few months ago aiming to give a microeconomic basis for exploring the reasons and structure of aggregate inventory behavior (with special reference to the inventory cycle). This paper is intended to give a summary of the results according to one special aspect used in the first phase of the research.
II OBJECTIVES AND METHODS OF RESEARCH II.1 Objectives
The main questions which we plan to investigate are the following: * I’m indebted to I&v&n Abel and ViktSa
Dalkb for their
many suggestions and other extremely valuable assistance. The computatioR~ work has been carried out by L&s&5 Csexj&s, whd also deserves special thanks.
Budapest. Hungary
(i) How can the inventory behavior of companies be characterized in time and structure? (ii) Which are the main microecooomic influencing factors of company inventory behavior? (iii) What connections can be found between inventory formation on the macro and micro levels? (iv) How do the basic marcoeconomic processes influence company inventory behavior? (i) How can the central (government) regulation influence the inventory behavior of companies and what kinds of feedback are there?
II.2 Methods employed
The research is to be carried out by using three basic approaches: -
-
statistical analysis case studies interviews
This paper is restricted to discussing part of the results of the statistical analysis. The two other methods--case studies and interviews-are for both checking and the results of the statistical approach. Detailed case studies of nineteen companies have been written by managers, discussing the inventory formation of their companies from 1968 to 1984 and giving the reasons for the various changes. Over twenty interviews with top managers and leading economists working for government organizations have been carried out and more are planned to explore the nume~~lly non-expressible facts and inte~lations.
28 11.3The statistical data base The data base we use is the data bank of the annual balance data of all Hungarian companies, available since 197 1. This is an extremely wide and valuable data set, the use of which, however, requires special attention first of all because of its bulk. The first step of the statistical work was to designate those data which should be used in the analysis. we have restricted our research to First, industry-all other sectors (agriculture, trade, etc.) have been left out. This step was justified by’two aspects: (i) We wanted to keep the analysis within limits which we thought we can handle. (ii) The share of industry from the total inventory stock is over one third, so it is definitely the most important sector which determines much of the factors influencing inventories in other sectors. Based on our preliminary considerations 39 original variables and 52 derived variables (indeces) have been chosen for the analysis. Since the number of industrial companies is fluctuating at about 1100 each year, we have a three dimensional block of data of the size 1100 x 91 x 14. III THE STRUCTURE OF INVENTORY STOCK AND INVENTORY INVESTMENT After carrying out many elementary statistical operations we decided to first explore the structure of annual inventory investment and of inventory stocks. This paper provides the result of this analysis. For the investigation we have decided on selecting some basic aspects which can be measured using our data base. So we characterized each company in each year with a twelve element vector, each element of which expresses and measures one of our characterizing aspects. The following aspects have been considered (the definitions are detailed in Chapter 111.2): 1 ownership: state companies vs. cooperatives 2 type of industry: extracting (mining) vs. manufacturing industry
3 branch of industry (based on the Hungarian statistical system) 4 size of company (characterization by number of employees and total sales) 5 market orientation (selling on internal, and/or COMECON and/or Western markets) 6 market share (proportion of sales from the total sales of sub-branch) 7 growth rate (this and all further characterizations are based on the relation to the industrial average) 8 redistribution rativthe effect of taxes and subsidies paid and received 9 profitability: annual profit per invested capital 10 inventory turnover 11 inventory investment ratio (annual inventory investment/initial inventory) 12 inventory structure (the ratio of input inventories, work-in process (WIP) and output inventories). An analysis of the data structure above aspects will be carried “sample” years. As a first step compared the data for the last two period examined, 1983 and 1984.
according to the out for several we studied and years of the time
III. 1 General conclusions from the structural analysis Three important general consequences can drawn from these first steps of the analysis:
be
1 The structure of the wole sample is extremely stable from two important points of view. (i) The distribution of both the inventory stocks and inventory investments. We have drawn about 600 histograms of inventory stocks and about 300 of inventory investments, in very different groupings and there could hardly be found any other distribution than the following patterns:
29 The most striking experience was to see that while there has been a permanent and high inventory buildup in Hungarian industry during the period examined, in each year and each group almost half of the companies actually decreased their inventories. This fact was unexpected by all experts when first discovered. The histogram of inventory stocks shows the concentration of inventories: a few companies hold the majority of stocks, again considering each category. (ii) The structure of inventory stocks by stage of manufacturing has been the other very stable element of all investigations. It has been long known that the industry as a whole has a structure of inventories (7l-72% input, l7-18% WIP, I l-12% output inventories) which does not change in time. But it was not clear that this is valid almost also at company level-at least in our analysis we had a rather similar structure in almost all cases. This structure is a consequence of market conditions in Hungary (namely, the general overdemand in the vast ma,ority of sub-markets). We all know the importance of its effects-but it was inseresting to see how strongly it influences the whole inventory system. 2 In most analyses one could easily follow and explain the behavior of input and WIP inventories and their changes. However, output inventories in most cases showed very irregular, sometimes even chaotic behavior. This is a warning that even though output inventories have the smallest share of the total, their behavior can be a very important signal of economic events. 3 There are some aspects of the analysis (or, on the other hand, some groupings) in which case the relative standard deviation is small-while in some other cases there are only a few companies around the average. In the first case one can define a company which is in some respects “typical”: in the second case it would be a mistake, since no or only a few actual companies can be ordered to the average. This fact is very important in Hungary where the central government tries to influence the inventory behavior of the companies with financial regulators the values (ranges, etc.) of which are calculated on an “average” basis. Quite naturally, the effect of
such a regulator
will be completely
different in a case
when it is influencing an aspect where there are many “average” companies compared to the other case, when there are no such companies. Here we just mention that those large companies which mostly influence the overall inventory situation in Hungarian industry can hardly be regulated by such general
rules anyway.
III. 2 Characteristics of the data set by the twelve aspects In the following, we detailes of the analysis we can use the above shall follow these step I Ownership:
shall give the most important carried out. As a framework twelve aspects and thus we by step.
state companies
vs. cooperatives
From the total number of companies (I 148) there were 541 state owned (47. I %) and 607 cooperative (52.9%) companies in 1983. The proportion of the companies in the two groups did not change during the 1971-84 period. The main conclusion is that from our point of view it is enough to analyse the state companies for two main reasons: - The share of the state companies from the total inventory stock is over 80%, which means that their behaviour has a decisive impact on the inventory cycle; - the structure of inventory stock and inventory investment in the years examined (1971, 1977, 1983, 1984) is so close to each other that the data of cooperative companies can be roughly considered a scaled-down equivalent of the data of state companies. From now on all statements refer to state companies only. 2 Type of industry: extracting vs. manufacturing industry
(mining)
The vast majority of companies belong to the manufacturing industry (over 900/,). The average size of companies is much larger in the first group, consequently inventory stocks are higher as well.
30 The structure of inventory investments is entirely different for the two groups in a given year, so this aspect of grouping seems to be relevant when examining inventory behavior.
TABLE
1
Inventory stock in the average the end of 1984
companies
Total state-owned industry
branches
Without
largest
inventory
holders
at
(20% of all
3 Branch of industry According to the Hungarian statistical system, the following eight branches are considered: 1 mining and drilling 2 electrical energy production 3 metallurgy 4 machine (engineering) industry 5 building material industry 6 chemical industry 7 light (textile, leather, wood etc.) industry 8 other industries. The structure of inventory investments is different in the various branches by stage of manufacturing (i.e. input, work-in-process, output inventories) and from year to year. These differences are smoothed out over the years; this isshown by the rather stable structure of inventory stocks. The ratio of inventories by stage of manufacturing can be considered as a kind of “norm” or “standard” characteristic of the given branch. In examining the macro cycles, inventory investment by branches is an important factor-partly because of the above statistical facts and partly because government control is to a great extent practiced by branches-and this control has an extremely important influence on inventory behaviour. An interesting discovery was that if the top 20% of the companies, i.e., the biggest ones are left out of the analysis, the average inventory levels tend to be very even (Table 1). This fact is very important given that government regulations (mainly financial) generally aim at the “average” companies. Our results show that this type of control can be justified from this point of view only provided that the different treatment of the large companies can be ensured. However, it can be easily seen that this way only a relatively small proportion of the total stock (28.8%) can be controlled. So this regulation can be efficient to some extent from the point of view of smooth operation
in various
companies)
Industry
Total
Average
No. of
Average
No. of
inventory
com-
inventory
com-
stock
panies
stock
panies
(mFt)
left out
(mFt)
Mining
25
463
11
188
Electricity
22
371
2
254
Metallurgy Machine
24
954
12
150
172
492
50
163
39
223
116
Building materials
58
615
22
147
Light
164
200
12
127
Other
37
2s
0
25
Total
541
Chemical
205,349
112
59,095
(with the condition mentioned), but not in controlling total inventory investment in industry. This is one of the failures of our government control system. 4 Size of companies The definition of the “size” of a company can be very different. The following classification was used: Large companies: - number of employees exceeds 15,000 persons, or - total sales exceed 4 billion Forints. Small companies:. - number of employees is less than 500 persons, or - total sales are less than 0.5 billion Forints. companies: Those for which none of the above criteria hold. According to this classification we have 385 small, 87 average and 74 large companies. Average
31 The F-tests show that this is an extremely s@nificant classification. This is one of the few groups, where even the histograms of inventory stocks (by stage of manufacturing and by years) are different. The distributions of small companies show the regular pattern, while those of the average and large companies are relatively even. (The histograms of inventory investment show the “regular” pattern). It is interesting that the total inventory investments in both years are strongly correlated (rb0.8) with the investments in input stocks in case of the large companies, with the investments in output stocks at the small companies, while at the average companies the correiation of total inventory investment was high with the input stock investment in one year and with the work-in-progress in the other year.
TABLE 2 Average inventory stock and investment in the various groups according to market orientation Million forints 1984
1983
Market
Inventory stock
Inventory invest_ ment
Inventory
Inventory investstock
ment
Internal sales only
125
9
128
10
COMECON export
111
12
208
11
Western export
221
25
246
32
Export in both relations
581
100
589
106
5 Market orienfurion In this respect we have ~sting~sh~ four groups of companies - sales only in the internal market - export only within COMECON countries (besides domestic sales) - export only to Western countries - export to both West and COMECON. In the various groups one finds 179, 27, 77, and 258 companies, respectively. This proved to be again a very important classification. Both the inventory stock and the inventor investment at the average companies is penally the same within one group for the different years, while there is a large difference among the groups (Table 2). This is, of course, in close connection with the fact that export orientation is more common in the case of large companies. The difference in the structure of inventory stocks between the two large groups is striking. Those companies which sell only on the domestic market practically hold no output stocks, and their work-inprogress is also minimal, Both types of stocks are considerably higher at the exporters (Table 3). This is a direct consequenoe of the different delivery requirements of the domestic and the export markets.
6 Market share This factor has been measured with the proportion of the sales of a particular company from the total sales of its sub-branch of industry. The groups have been formed on the basis of this proportion being less than l/16; l/8; l/4; l/2; and greater than l/2.
TABLE 3 Inventory structure of companies of different market ovation Market orientation
Input stock %
Work-inQrogrws %
Output stock %
Companies selling on domestic market only
88.9
6.9
4.2
Exports
71.3
17.3
11.4
Examinations show that this classification is again in very close connection with company size. However, there is a great difference among the various groups in their structure of inventory investments, much larger than in case of the grouping by company size. The reason is yet to be explored.
32 7
Growthrate
The growth rate of the individual companies is measured in their relationship to the industry average. Namely, the following four categories have been applied : decreasing: growth rate 0 small: growth rate less than Z/3 industry average medium: growth rate between Z/3 and 4/3 average large: growth rate over 4/3 average It should be noted here that the same criteria have been applied for all the remaining aspects (8-12, without the 0 group at 10 and 12). The main observation is that companies experiencing different growth rates have basically the same level and structure of inventories+even though the status of a particular company is very transient from year to year. So this grouping is not significant for the whole sample but can be very significant for a particular company. The basic characteristic of this grouping is somewhat similar to the classification by branches from the point of view that there are great differences in annual inventory investments which are smoothed out over the years resulting in an even inventory level. 8 Redistribution
ratio
By “redistribution” here the net effect of state taxation and support is meant. If X’ denotes the profit of a company before taxes and receiving any subsidies and X, denotes the profit on the actual balance sheet, the following measure of redistribution (r) can be defined:
groups will have very similar distribution patterns both by years and by types of inventories. It is interesting that the companies in the smallest redistribution group hold the largest output inventories by far and their average is 4-5 times greater than that of the whole sample! (One straightforward explanation, which still must be checked: these are the companies which are left to themselves by the state, which forces greater market adaptibility on them, which makes higher output inventory a necessity.) 9 Profitability Profitability is measured by the ratio of profit (after redistribution) and total invested capital. It is a very important observation that this grouping is* investment are influenced by protitability in the case of Hungarian companies. The second interesting result is that the average inventory stock is higher in the groups of negative and low profitability. The structure of inventory is quite different in the companies showing a deficit than in any of the other groups (Table 4). 10 inventory
turnover
This was measured by the ratio of total inventories to total sales. This ratio is small when the turnover is high. TABLE 4 Average inventory stocks and their structure in groups according to provability Year: 1984
X,-X,
Groups
r = cx, + X,)/2
The effect of the level of redistribution on the general behavior and operation of the companies is tremendeous and we wanted to see its relation to inventory behavior. The most important observation is that redist~bution changes widely from year to year. A particular company can shift from the highest to the lowest group in one year. It is not really surprising that if the largest companies are left out, the four
Distribution
Average inventories
by stage
of manufacturing
(%)
(mW
Input
WIP
output
Deficit
402
65.4
21.9
6.7
Low profitability
412
73.5
16.5
10.0
profitability
373
75.0
15.3
9.7
High profi~bility
334
69.7
14.4
15.9
Average
l
Not
inventory.
significant:
neither
the
inventory
level
nor
the
33 The order of the various groups is the same for both years examined and for all types of inventories: higher turnover rate means lower absolute level of inventories. This is not absolute, but reflects the regular and stable structure of the inventories in Hungarian industry (Table 5). It can also be seen that companies with a low turnover hold high output inventories at the expense of input inventories. TABLE
5
Inventories
The internal structure of inventories is completely different in the two years examined, which definitely shows that a large number of companies go from one group to another each year (since the structure of inventories of a particular company normally does not change too much from year to year). This is one of the rare cases when not all the histograms are “regular” ones. For example, in both years almost all companies which decreased total inventories (group 1) decreased their intput inventories as well (while their WIP and output inventories show the regular pattern).
in groups according to inventory turnover
Year: 1983
12 inventory strwtwe Type of inventory
Inventory turnover
High Average
WIP
Input
Total
output
mFt
%
mFt
%
mFt
%
mFt
176
72.1
38
15.6
29
11.9
244
266
75.1
56
15.8
31
8.8
354
330
68.2
70
14.4
83
17.1
484
In almost all groupings we found that they are significant for the inventory investment (even in those cases when not significant for inventory stock); this classification is an exception, which is rather surprising. I1 Inventory investment ratio This was measured by the ratio of inventory investment in a particular year to the initial inventory of that year. It is interesting that in the group of “average” inventory investment there are only very few companies in both years examined (e.g., in 1983, the number of companies in the negative, small, average and high groups were 194,53,26,268, respectively) and this is all the more so, since we know that the distribution of companies by inventory investment is rather concentrated. This means that the average has a very high standard deviation and that inventory investment is not correlated with the initial inventories, which is in fact the case for all groups except, not surprisingly. in the case of the group of average ratio.
The internal structure of inventories was measured by the ratio of input inventories to the total inventories. We used three categories (low, average, high) based on the usual criteria. The groups have an extremely interesting structure: in the group of high input inventory proportion the WIP inventories are very low, compensating the high input inventories to the lefel that the output inventories have the same ratio. The average inventory is much lower in the group of low input inventory ratio, while practically the same in the two other groups (in 1984: 256, 453, 441 mFt, respectively). Inventory investments in the two years examined happened in a very different structure-in general, almost all structures of this classification are rather mixed, with less regularity than in most other cases. IV CONCLUSION
The structural analysis reported here is only the very first step of an extended study. However, it has already provided (i) some important starting points for further analysis (ii) a fevi conclusions of interest for economic policy makers. The main general issues derived from the analysis are given in Chapter III. 1. The detailes given in 111.2.(i) prove that the set of the twelve characterizing aspects was well selected since significant conclusions can be drawn by their application (ii) provided good points for further statistical analysis when more sophisticated methods will be used.
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