روش‌های ترکیبی جدید CB-RAS و CHARM-RAS برای محاسبه جدول داده-ستانده منطقه‌ای و سنجش خطاهای آماری (مطالعه موردی: استان گیلان)

نوع مقاله : مقالات پژوهشی

نویسندگان

• علی اصغر بانوئی ¹
• پریسا مهاجری ²
• فاطمه کلهری ¹
• زهرا عبدالمحمدی ²
• زهرا ذبیحی ³
• سحر محمدکریمی ²
• مریم پارسا ²

¹ دانشگاه علامه طباطبائی

² علامه طباطبایی

³ دانشگاه علامه طباطبایی

https://doi.org/10.22067/erd.v24i13.60689

چکیده

از میانه قرن بیستم تاکنون، انواع روش‌های غیرآماری در محاسبه ضرایب داده-ستانده منطقه‌ای (RIOCs) و محاسبه جداول داده-ستانده منطقه‌ای (RIOTs) توسط تحلیل‌گران اقتصاد داده-ستانده منطقه‌ای معرفی شده‌اند. در یک طیف، انواع روش‌های سهم مکانی قرار دارند که کانون توجه آنها محاسبه RIOCs است و تراز RIOTs منوط به پذیرش دو پسماند بردار صادرات و بردار ارزش‌افزوده بخش‌های منطقه است. طیف دیگر را روش‌های تراز کالایی (CB) و مبادلات تجاری دوطرفه (CHARM) تشکیل می‌دهند که خاستگاه اصلی آنها، محاسبه RIOTs است که در آن، منظور کردن پسماند ارزش‌افزوده در تراز RIOTs نقش کلیدی دارد. در این مقاله، برخلاف تعداد معدودی از پژوهش‌های انجام گرفته در ایران، نشان داده می‌شود که بکارگیری روش‌های CB و CHARM، ارقام بردار ارزش‌افزوده در حساب‌های منطقه‌ای مرکز آمار ایران را به طور ناخواسته تعدیل می‌کند. این مشاهده، یک سوأل اساسی را پیش‌روی نگارندگان مقاله قرار می‌دهد: چرا بایستی آمارهای رسمی ارزش‌افزوده بخش‌ها را تعدیل نمود؟ برای برون‌رفت از این نقیصه و پاسخ به سوأل مطرح شده، روش‌های ترکیبی جدید CB-RAS و CHARM-RAS پیشنهاد می‌گردد. روش‌های CB، CHARM، CB-RAS و CHARM-RAS در کنار جدول ملی، منطقه‌ای و حساب‌های منطقه‌ای سال 1381 استان گیلان مبنای محاسبه RIOTs استان قرار می‌گیرند. یافته‌های کلی نشان می‌دهند که نخست، روش‌های CB و CHARM، GDP استان را 4/2 درصد کم برآورد می‌کنند. دامنه تعدیل ارزش‌افزوده بخش‌ها قابل ملاحظه است به طوری‌که بخش صنایع وابسته به کشاورزی، 5/9- درصد و بخش معدن 6/54+ درصد را نشان می‌دهد. روش‌های پیشنهادی این نارسائی را برطرف می‌کند. دوم، پنج روش آماری MAD، RMSE، TIL، STPE و WAD مبنای سنجش خطاهای آماری بین ماتریس‌های ضرایب فزاینده عرضه مستخرج از روش‌های ترکیبی CB-RAS و CHARM-RAS با ارقام متناظر واقعی قرار می‌گیرند. یافته‌ها نشان می‌دهد که خطاهای آماری در روش ترکیبی CHARM-RAS به مراتب کمتر از سایر روش‌ها است.

کلیدواژه‌ها

• روش تراز کالایی
• روش CHARM
• جدول داده-ستانده منطقه‌ای
• روش ترکیبی CHARM-RAS

عنوان مقاله [English]

New Mixed CB-RAS and CHARM-RAS Methods for the Estimation of Regional Input-Output Table and Assessing Statistical Error: A Case of Gilan Province

نویسندگان [English]

• Ali Asghar banouei ¹
• parisa mohajeri ²
• fatemeh kalhori ¹
• zahra abdolmohammadi ²
• zahra zabihi ³
• sahar mohammad karimi ²
• maryam parsa ²

¹ Allameh Tabataba'i

² allameh tabataba`i

³ allameh tabataba`i

چکیده [English]

Since the 1950s, many types of non-survey methods have been introduced by regional input-output economists for the estimation of Regional Input-Output Coefficients (RIOCs) and Regional Input-Output Tables (RIOTs). On the one hand, there are different kinds of location quotient methods (for example, , , , , , , and ) which focus on estimating RIOCs and balancing RIOTs and which require acceptance of 2 types of residuals: 1)exports of a region to other regions and the rest of the world, and 2)regional sectoral value added. On the other hand, there are Commodity Balance (CB) and Cross-Hauling Adjusted Regionalization Method (CHARM) which concentrate on estimating RIOTs and the regional sectoral value added which play a key role in balancing RIOTs. The application of the CHARM method is not appropriate for estimation of RIOTS in Iran. The main reason is that the use of CHARM method needs two residuals for balancing the RIOT. One of these residuals is the trade balance (exports- imports) and the second one is regional sectoral value added and the regional GDP. Using the former as a residual seems to be plausible for row balancing of RIOTS, whereas the latter unnecessarily adjusts the regional sectoral value added as well as regional GDP. This residual is not appropriate for countries like Iran which have regional accounts. Since 2000, the statistical center of Iran (SCI) has been providing regional accounts for 31 provinces. It comprises of 72 regional sectors which are comparable with national account classifications. The regional accounts of SCI provide us with sectoral intermediate inputs, sectoral value added and sectoral output for 72 sectors for these 31 provinces. If we use CHARM method for regionalizing NIOTs, the regional sectoral value added and the regional GDP given by the SCI have to be ignored due to the inevitability of residual regional sectoral value added.
In this paper, we have shown that the sectoral value added in regional accounts of Iran is adjusted involuntarily due to the use of CB and CHARM for estimation of RIOTs. This issue raises an important question: why should theofficial regional sectoral value added be unnecessarily adjusted? To tackle this problem, the new mixed CB-RAS and CHARM-RAS method is proposed. The new proposed mixed method only takes regional trade balance as a residual and uses the official regional sectoral value added of the regional accounts that have been provided by the statistical center of Iran.
For the application of CB, CHARM, CB-RAS and CHARM-RAS methods, the following data were utilized. 1) Based on the survey- based NIOT of 2001, we updated two NIOT for the year 2002. 2) The regional sectoral intermediate inputs, value added and outputs of Gilan provinces were directly taken from the regional accounts of the SCI. 3) The survey- based RIOTS of this province for the year 2002 were obtained. In order to make the applications of the two methods manageable, the data were aggregated into seven sectors: agriculture, mining, agro-based industries, other industries, water, electricity and gas, construction and services. Based on the CHARM and the proposed mixed CHARM-RAS methods, RIOTS for the province of Gilan for 2002 were generated. The results indicate that the official total value added (GDP) of Gilan province in 2002 was 23401590 billion rials, whereas the corresponding estimated figure derived from the CHARM and CB methods was 22847050 billion rials. This suggests that the CHARM and CB methods underestimate the GDP of Gilan province by 2.4 percentage. Moreover, The regional sectoral value added deviations were calculated. The minimum deviation for agro-based industries was -%9 and the maximum deviation was %+54.6 for mining. To fill this gap, we have proposed the new mixed CHARM-RAS and CB-RAS method to generate RIOTs for the this province. Applying these methods no longer requires the unnecessary adjustments , the regional GDP, and the use of official data. Therfore, the new mixed method eliminates the shortcomings of the previous methods. Moreover, five conventional statistical methods, namely MAD, RMSE, TIL, STPE and WAD were utilized for assessing statistical errors between supply multiplier matrixes which are derived from the new mixed CB-RAS and CHARM-RAS method corresponding to the official figures. The results show that the degree of accuracy of the supply multiplier matrix of the mixed CB-RAS and CHARM-RAS method in all of the five statistical methods is much closer to the official figures than the one gained using CB and CHARM methods independently. Hence, the statistical error of CB-RAS and CHARM-RAS method is much less than the statistical error of CB and CHARM method in supply multipliers.

کلیدواژه‌ها [English]

• Commodity Balance Method
• CHARM Method
• Regional Input-Output Table
• Mixed CHARM-RAS Method

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