SECTION X: EMPIRICAL ANALYSIS
10.6 Interpretation on Empirical Findings
determination as 0.867 (see Diagram 9). Thus, we may say that the empirical implementation in this aspect is quite satisfactory.
Diagram 9
10.6 Interpretation on Empirical Findings
From the above analysis on empirical data of 20 localities, a major finding is that the class oriented agrarian land distribution reflects institutional arrangements adopted by an agrarian community to accommodate its labor force to land utilization under given circumstances. The two predominant patterns immediately reveal whether the arrangement through land tenancy has been adopted or not in a locality. We shall try to provide some interpretations on the empirical findings here.
From most literature dealing with the subject of land tenancy in the early twentieth-century China, we can derive two generations: (1) the prevalence of land tenancy differed pronouncedly in the North and the South, and even within the same province and (2) the land tenancy was high in areas which were more commercialized.13
The empirical findings from 17 villages and 3 towns in 12 counties of Kwangtung province demonstrated conclusively that variations did exist in the same
13 See for example, R. H. Tawney, Land and Labor in China (original, 1932; reprint, Boston, 1966), pp.
63-69. Dwight H. Perkins, pp. 85-110; Joseph W. Esherick, “Number Games: A Note on Land Distribution in Pre-revolutionary China,” Modern China, Vol. 7, No. 4 (October, 1981), pp. 387-411.
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province. Thus the first generalization mentioned above is proved valid. We should only concentrate on testing the validity of the second generalization through the use of other available data organized from the same land records.
The first available data other than land acreage is land price. If it is reasonable to assume that the unit price of land reflects the fertility of land and that the higher the fertility of land in a place the more commercialized it is, then the unit price of land may be taken as an indicator for commercialization. By using this indicator, we should be aware of the fact that land price may be varied to some extents in different areas. For example, among the localities we have studies for this paper, the unit price of land at five villages in Ch’eng-hai 澄海 county is much higher than that in other counties. Of course, Ch’eng-hai county is nearby a commercial center, Shan-t’ou 汕 頭 (Swatow), and this may be a reason for its high price of land. However, we have also investigated a few villages in P’an-yü 番禺 and Nan-hai 南海 counties which are nearby another commercial center, Canton, and yet the land price at these villages are not particularly high. Due to these variations, the results of correlation analysis may be affected (see Table A9).
For example, if we take the class membership as a proxy for labor force and let the sum of numbers of landless tenant (N1) and one half of landed tenant (N3/2) be a proxy for the tenant labor force (Nt), we have found that there is a rather weak positive relationship between the tenant labor force (Nt) and the unit price of land (p);
the coefficient of determination is only 0.155 (see Diagram 10).
Diagram 10
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If we should look into land price for any further interpretation, we may have to try from another angle. For instance, we are able to arrange the data of land price corresponding to class land ownership and calculate the unit price of land owned by each sub-class as shown in Table A9. Despite the variations among localities, we can see that among the sub-classes of a locality, the unit price of land owned by landed tenant (p3) is the lowest in 12 localities and the next lowest in 4 localities. This may be interpreted as that when a landless tenant has accumulated enough savings to purchase land to promote himself into the status of a landed tenant; he is most likely to buy the cheapest land. However, this interpretation will not be applicable to the remaining 4 localities where the unit price of land owned by sub-class 3 is the highest or the next highest.
Another dimension of the data available from the land records is fragmentation of land. If we assume that in a place of higher land tenancy there will be fewer plots of minimum size land and hence it is more difficult for the poor tenant to purchase land, we may find a negative relationship between the prevalence of land tenancy and land fragmentation. When the concentration index 9x) is taken as a dependent variable and the ratio of minimum size plots to the total plots of land (m) is taken as an independent variable, the scatter diagram reveals that there is negative relationship between these two variables. A regression by the ordinary least square method produces a result of coefficient of determination as 0.0583 (see Diagram 11). But it should be noted that this result is obtained when one of the extreme case (m = 0.424) is deleted.
Diagram 11
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Finally, the last dimension of data available from the land records is rent.
Except for the case of Chine-ts’un where only plots rented out have rent in records, for all other localities, rent is recorded for every plot of land regardless whether it is rented out or not. For this reason, we tend to suppose that the recorded rent may be the rent paid by the tenant to the owner. Moreover, in four localities (P’ing-kung, Ch’ing-p’ing, Li-lin, and Shang-hsia-wo) the recorded rent is in terms of kind with different unit of accounting and this increases difficulties of analysis.
Since we are not able to find any significant relationship between the unit rant computed from the records and the concentration index (x) using the data of 15 localities, at this stage, we should say that the recorded rent may not be used directly to test whether it is a reflection of commercialization and is related to land tenancy.
Using the pertinent data from the same land records, we have tried in above to test the hypothesis on the relationship between commercialization and land tenancy.
We have found that at least from the aspect of land price, commercialization and land tenancy were positively related and from the aspect of land fragmentation, they were negatively related, although the degree of correlation were, in both cases, quite weak due to variations in the original data.
We should also consult other documents to elaborate our interpretation.
However, most local gazetteers of the counties related to this study do not provide detail information down to the village level. For this reason, these findings from the land records are all the more valuable as they add new historical evidences that are not available elsewhere.
CONCLUDING REMARKS
Starting from an abstract concept of agrarian land structure, we have set up a theoretical framework for empirical analysis n land records of Kwangtung in the 1930s. This theoretical framework may be applied to analyze the agrarian land structure in any society as long as necessary statistical data are available.
Empirical analysis and comparison on data organized from the land records of 20 localities demonstrate that the agrarian land distribution is a rather complex framework.
The empirical implementation to the theory has produced quite satisfactory results. From the shapes of Lorenz curve of class land ownership and pseudo Lorenz curve of class land cultivator-ship, we have been able to discern two predominant patterns, the ICP pattern and the LTP pattern, corresponding to certain values of G and G*. Moreover, there is a positive relationship between the two indicators of land tenancy, R* and x. In addition, the hypothesis on the relation between
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commercialization and land tenancy has been tested through using pertinent data available from the same land records. Thus the intrinsic consistence of the land records is proved.
Finally, it should be emphasized that this voluminous (a total of 3,333 volumes) land records of Kwangtung province are valuable for understanding the agrarian land structure in the 1930s, a critical era of modern land reform. Materials of 20 localities investigated for this study are accounted for only one percent of the whole collection.
However randomly and preliminary, the empirical analysis has produced quite good results. Thus it is indeed necessary and worthwhile to further investigate systematically into this huge collection.
APPENDIX
To construct an agrarian land structure for a rural community, it is required to have primary statistical data that reveals the family identity of owner and cultivator of every tract of land in that community. Fortunately, the Taiwan Branch of the National Central Library in Taipei has a collection of Kwangtung land records which provides the necessary data for this study.14
For our purpose, the original records are first transcribed into numerical code and then computerized. For each plot of land, the original records include seven variables: (1) location, (2) grade of land, (3) acreage of land, (4) price of land, (5) rent of land, (6) owner, and (7) tenant (i.e., cultivator). Before the original data are organized into useful statistical data, it is necessary to identify each owner and cultivator according to the classification shown in Table 2 in the text. Since an owner (cultivator) may own (cultivate) more than one plot of land and some owners may also cultivate their own land or other people’s land, in original records the same owner (cultivator) may appear here and there over a wide range of land plots, thus it is necessary to look through carefully all plots in a village to identify the type that one may belong to. With the owner denoted as variable 6 (v6) and the cultivator as variable 7 (v7) for each plot of land, the rule of identification is as follows:
Type I: v6 ≠ v7 where all v7 only appear as cultivator.
Type II: v6 = v7.
Type III: v6 = v7 and v6 ≠ v7 where all v6 in the latter are not the same as v6 in the former.
14 For details of this collection see, A Catalog of Kuang-tung Land Records in the Taiwan Branch of the National Central Library, 1975.
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Type IV: v6 ≠ v7 where all v6 only appear as owner.
Type V: v6 = v7 and v6 ≠ v7 where all v6 are the same.
Type VI: v6 = v7 and v6 ≠ v7 where at least one v6 is not the same.
With the type identification for each owner and cultivator, the eighth variable, namely, the relationship between owner and cultivator of every plot of land can be obtained. With the eight variables ready for every plot of land, then the statistical data can be organized corresponding to types of families. The statistical data needed for analyses in the text are arranges in ten tables as follows:
Table A1: Land Acreage Corresponding to Types of Families: Elements for Aggregated Agrarian Land Structure
Table A2: Reclassification of Type VI Families
Table A3: Land Owning and Cultivating Acreage of Five Sub-classes Table A4: Class Membership
Table A5: Class Land owning and cultivating Structure Table A7: Degree of Class Land management
Table A8: Some Important Indicators Table A9: Land Price
Table A10: Minimum Size Land
In Tables A1 and A2, localities are arranged by counties just to show their administrative affiliation. The last three localities are towns while others are villages.
In Tables A3 and A10, localities are arranged corresponding to variations of class affluence ranking order as discussed in the text.
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Table A1: Land Acreage Corresponding to Types of Families: Elements for Aggregated Agrarian Land Structure
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Table A2: Reclassification of Type VI Families Locality
Consolidated into Type III Consolidated into Type V
N A C P N A C P
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Table A3: Land Owning and Cultivating Acreage of Five Sub-classes Unit: mou
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Table A5: Class Land Owning and Cultivating Structure Locality
Class Land Owning Fraction (gi)
g1 g2 g3 g4 g5
Class Land Cultivating Fraction (ti)
t1 t2 t3 t4 t5
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Table A6: Class Affluence and Land Management (Unit: mou) Locality
Class Affluence (Ui) Endowment
Ratio
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Table A7: Degree of Class Land Owning and Management
Locality
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Table A8: Some Important Indicators
Locality G G* x R*
1.Pai-ch’i 0.428 -0.190 1.44 0.546
2.Ta-ch’e 0.343 -0.473 2.38 0.837
3.Shan-chou 0.451 -0.468 2.04 0.895
4.T’ang-t’ou 0.450 -0.089 1.20 0.511
5.Hsien-men 0.356 -0.541 2.52 0.901
6.Ch’ih-chiao 0.396 -0.537 2.36 0.907
7.P’ing-kung 0.334 -0.130 1.39 0.525
8.Ma-lan 0.392 -0.254 1.65 0.654
9.P’ing-hai 0.462 -0.451 1.98 0.837
10.Chien-ts’un 0.553 -0.238 1.43 0.598
11.San-tai-mei 0.469 -0.475 2.01 0.938
12.Hsien-shih 0.507 -0.385 1.76 0.934
13.Nei-ch’i 0.503 -0.299 1.59 0.676
14.Ch’ing-p’ing 0.466 -0.388 1.83 0.850
15.Nan-sha 0.535 -0.428 1.80 0.886
16.Ho-heng 0.327 0.224 0.31 0.212
17.Hsieh-ts’un 0.304 0.082 0.73 0.419
18.Ma-an 0.251 0.216 0.14 0.166
19.Li-lin 0.135 0.028 0.79 0.135
20.Shang-hsia-wo 0.123 0.179 -0.46 0.068
47 11.San-tai-mei 138.36 128.86 139.09 150.78 138.88 12.Hsien-shih 118.10 135.56 134.88 131.75 134.10
13.Nei-ch’i 33.86 30.66 31.17 32.32 31.71
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*In these two localities, no plot of land is larger than 1 mou, thus 0.01 taken as a criterion rather than 0.1.
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REFERENCES
Chen Han-seng, Landlord and Peasant in China: A Study of the Agrarian Crisis in South China, New York, 1936; reprint 1973.
Esherick, Joseph W., “Number Games: A Note on Land distribution in Prerevolutionary China,” Modern China, Vol. 7, No. 4 (October), pp. 387-411.
Fei, John C. H., Ranis G. and Kuo, S., Growth with Equity: The Taiwan Case, New York and London, 1979.
Fincher, John, “Land Tenure in China: Preliminary Evidence from a 1930’s Kwangtung Hillside,” Ch’ing-shih wen-t’i, Vol. 3, No. 10 (November 1978), pp.
69-81.
Hinton, William, Fanshen: A Documentary of Revolution in Chinese Village, Monthly Review Press, 1966.
Liang Keng-yao, “The Land distribution and Tenant System of the Southern Sung,”
(in Chinese), Shih-huo Monthly, Vol. 7, No. 10 (January 1978), pp. 500-524.
Myers, Ramon H., The Chinese Peasant Economy: Agricultural Development in Hopei and Shantung, 1890-1940, Cambridge, Mass., 1970.
Perkins, Dwight, H., Agricultural Development in China, 1368-1968, Chicago, 1969.
Tawney, R. H., Land and Labor in China, 1932; Boston, 1966.
The Taiwan Branch of the National Central CLibrary compiled with an introduction by Roy Hofheinz, A Catalog of Kuang-tung Land Records in the Taiwan Branch of the National Central Library, San Francisco, 1975.
Wilkinson, Endymion trans, Jing Su and Luo Lun, Landlord and Labor in Late Imperial China, Case studies from Shandong, Cambridge, Mass., 1978.
摘要