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(Avecedo, Pamela E. and Emily Cabanda) An Empirical Analysis of TFP Gains in the Philippine Food Processing Industry: A Multi-criteria Approach (Chiu, Candy Lim and Emilyn Cabanda) Motivational and Environmental Factors Influencing Family Business: Evidence from a Study of Chinese-Filipino Entrepreneurs in the Philippines (Chiu, Tzu-hsiu) Public Secrets: Geopolitical Aesthetics in Zhang Yimou’s Hero (Cunningham, Eric) Ecstatic Treks in the Demon Regions: Zen and the Satori of the Psychedelic Experience (Karanth, Dileep) The Indian Oboe Reexamined (Magno, Augustus and Emilyn Cabanda) Asian Development Bank Assistance after the Asian Financial Crisis: An Empirical Analysis of Its Financial Resources and Operational Activities (Moro, Pamela) Defining the Classical in Studies of South and Southeast Asian Music: A Review and Evaluation of Pertinent Scholarship (Nguyen, Keaton) The Agency of Keitai (Sinclair, Paul) The Modern Chinese Language and its Changing Status in the Japanese University (Tillack, Peter) Out of Place: Effaced History, Embodied Memory in Gotô Meisei’s "Nameless First-Lieutenant's Son" Esterline Winners:
(Dewell, Christopher) Going Abroad: Japanese Travel to Chinese Nagasaki in the Tokugawa Era (Wood, Michael) Masculinism, Colonialism, and the Late Edo Castaway Narrative: Japanese Accounts of Port Brothels in the Pacific

An Empirical Analysis of TFP Gains in the Philippine Food Processing Industry:

A Multi-criteria Approach

By

Pamela E. Avecedo [1] and Emilyn Cabanda [2]

University of Santo Tomas [3]

 

This paper investigates the total factor productivity (TFP) performance of 29 firms in the Philippine food manufacturing industry from 1997 to 2001. It identifies the sources of TFP growth and assesses TFP growth changes in a sample of small, medium, and large-sized firms, and in the industry. Data envelopment analysis (DEA) approach is used to estimate the changes in the production frontier. The Malmquist productivity index has decomposed total factor productivity into technological change (TECHCH) and technical efficiency change (EFFCH). TECHCH implies shifts in the frontier or innovation while EFFCH implies catching up to the frontier. Empirical results suggest that the Philippine food sector features low productivity growth. Catch-up is the main driver for TFP growth, while poor innovation pulls down the productivity growth. Large-sized firms have the highest TFP growth, compared to small and medium-sized firms, which is boosted by its high EFFCH score. However, small and medium-sized firms are more innovative, which contributed largely to their TFP growth. Hence, the determination of sources of TFP growth provides more accurate information for policy implications related to boosting productivity in the food sector. Lastly, we also provide new findings that productivity and efficiency growth are significantly affected by firm size.

I. Introduction

The most recent commonly used method for productivity measurement is the Data Envelopment Analysis. Charnes et al. (1978) was the first to apply the DEA method for

measuring efficiency for non-profit organizations in the U.S.. Charnes et al. (1978) proposed a model which had an input orientation and assumed constant returns to scale (CRS). After Charnes et al.'s study (1978), DEA was populary used by many scholars to measure efficiency.  Previous studies that used DEA in measuring bank efficiency were: see Grigorian et al. (2002); Rebelo et al. (2000); Griffel-Ttjie and Lovell (1997); Fukuyama (1995); Miller and Noulas (1994); Banker et al. (1984); Tser and Tsai (2000); and Quey (1996).

Several scholars have also employed DEA in various sectors such as telecommunications and electricity (Madden and Savage (1999); Coelli (1998)); manufacturing (Mahadevan (2002); Illueca and Lafuente (2003); Jayanthi (1996)); and cross-industries (Boussofiane et al. (1997)). This method is also applied to the service sector; schools/universities (Coelli et al. (1998); Abott and Doucouliagos (2002)); administrative regions (Pao et al. (1993)); vehicle inspections (Odeck (2000)); and hospitals (Chirikos and Sear (2000).

These previous studies are all helpful in offering a benchmark for measuring productivity, especially the use of DEA method in this research.  All identified variables such as inputs and outputs used are all consistent with those variables employed by previous studies in performing productivity analysis.

This paper calculates output-oriented Malmquist indices of Total Factor Productivity (TFP), technological change (TECHCH), and technical efficiency change (EFFCH) of the Philippine food processing industry. Unlike previous studies which dealt only with small versus large firms or by individual category or an industry as a whole, this study analyzed separately the three categories of firms, namely: small, medium, and large-sized firms and comparing their productivity gains from each other and pooling them together as a whole. Hence, this present study would fill in the gap in the analysis of the productivity performance, using three categories of firms. The results of this study add to the growing literature on efficiency and productivity performance and also for policy formulation purposes in the Philippines.

Apparently, performance of the Philippine food industry is not improving well.  Hence, this paper attempts to answer the following questions: (1) What are the sources of total factor productivity in the Philippine food manufacturing industry from 1997 to 2001? (2) What are the total factor productivity growth changes in selected small, medium, and large-sized firms and the aggregate of firms in the Philippine food processing industry over the period covered?

This study is intended for policymakers, investors, industry players, and researchers. Reported findings in this study serve as a guide for policymakers in determining productivity and competitiveness of industry players and the sources of productivity for policy formulation purposes. This study would also supply information to investors in their investment decisions in the food processing industry of the Philippines. The industry players are those who will benefit the most from this study since the results provide a benchmark for the industry. Lastly, the findings of the study  open new areas of future research in productivity analysis.

The rest of the paper is organized as follows. Section II provides a background on the Philippine food manufacturing industry. Section III describes the DEA framework and methodology.  Section IV explains the empirical results. The paper ends with conclusions and suggestions for further research in Section V.

II. The Philippine Food Manufacturing Sector

Food processing can be defined as any type of value addition to agricultural production starting from the post-harvest level. The following items are components  of the Philippine Processed Food Sector: fruits (juices, purees, concentrates); dried fruits (dried mango and banana chips); prepared/preserved fruits (nata de coco); meat and meat preparations; dairy products; cereal and flour preparations; vegetables; sugar and sugar preparations and honey; coffee; cocoa and tea; ethnic foods: sauces, condiments, spices and mixes; animal feeding stuff; beverages (e.g., beer, flavored beverages, sodas, whiskey, and rum); margarine, shortening, vegetable fats and oils; nuts and coconut products; and miscellaneous edible products and preparations (e.g., homogenized vegetables (soy bean paste, bean curd, bean cheese), food preparations, soup and broth, etc.). The food manufacturing (processing) industry contributes largely to the Philippines development for it promotes linkages and synergies among the three sectors of the economy namely: agriculture, industry and the services sector.

Food manufacturing accounted for 38 percent of industrial Gross Value Added (GVA) in 2002 and also accounted for an average of 53 percent of the personal consumption expenditure (NSCB, 2002). It also employs about 200,000 people (NSO, 2000). Thus, the food manufacturing sector makes a big contribution to the Philippine economy. It is also the leading industry in terms of number of establishments and employed the most number of workers. The Philippines is still a rural-based agrarian economy and the agricultural sector still shares, a significant proportion of GDP. Development and strengthening of resource-based industries such as food processing can bring immense benefits to the economy, such as raising agricultural yields, creating employment, and raising the standard of a very large number of people throughout the country, especially in the rural areas.

The Philippine food manufacturers/processors is composed largely of small-and-medium enterprises (SMEs), but there are at least five (5) large integrated food conglomerates that dominate the domestic market at present (FNRI, 1998). Most of the companies included in the study, especially the SMEs are entirely devoted to food processing. Some of the large-scale companies such as Del Monte Philippines are not just purely involved in food processing, but they have also their own plantations.

The Monthly Integrated Survey of Selected Industries (MISSI), conducted by the National Statistics Office revealed that the average growth rates of the Value of Production Index (VaPI) and Volume of Production Index (VoPI) of the food manufacturing industry for the period 1997 to 2002 were 10.2 percent and 6.36 percent, respectively (NSO, 1997-2002). For the period 1997-1999, both indices registered double digit growths; however, after 1999, growth rates were down to single digit. The average growth rate in value of net sales and volume of net sales for the same period were 14.89 percent and 11.95 percent, respectively.

Processed food exports also experienced decline from 1996 to 2002, with an average growth rate of -0.913 percent. But exports rose in 2002, with a growth rate of 5.31 percent (BETP, 1996-2002).  Among processed food exports, processed fruits represent 35 percent (US $ 205.94 M) of exports (BETP, 2002).  Major exports under this group include prepared/preserved pineapples, mixture of fruit, nata de coco and palm fruit, which account for 60 percent share of processed fruit export. Nuts and coconut products represent an 18 percent share (US$ 105.67 M).  The bulk of Philippine exports of processed foods are shipped to the United States, which represents a 36.89 percent share and is valued at US $ 217.04 M in 2002 (BETP, 2002).

Due to the significance of the food sector to the Philippine economy, it is the purpose of this study to identify the sources of productivity for the food manufacturing sector that would help in the formulation of strategies for its advancement towards a more productive and globally competitive sector (or be at par with the "world's best frontier/practice").

A study on competitiveness, benchmarking, productivity, and efficiency such as this one is just timely and significant for policymakers and industry players in this age of globalization. Globalization and liberalization pose as a threat to the Philippine food industry, with the influx of imported processed foods from other countries such as China, Japan, and the United States.  However, this threat can be turned into an opportunity, if the Philippine food processing industry makes necessary moves to become globally competitive.

III. DEA Framework and Model

The Data Envelopment Analysis (DEA) is a special mathematical linear programming model and test to assess efficiency and productivity. It allows use of panel data to estimate changes in total factor productivity and breaking it down into two components namely, technological change (TECHCH) and technical efficiency change (EFFCH  ).  

TFP growth measures how much productivity grows or declines over time. When there are more outputs relative to the quantity of given inputs, then TFP has grown or increased. TFP can grow when adopting innovations such as electronics, improved design, or which we call "technological change" (TECHCH). TFP can also grow when the industry uses their existing technology and economic inputs more efficiently; they can produce more while using the same capital, labor and technology, or more generally by increases in "technical efficiency" (EFFCH). TFP change from one year to the next is therefore comprised of technological change and changes in technical efficiency.

This study uses the output-oriented model of DEA-Malmquist to put much weight on the expansion of output quantity out of a given amount of inputs. Therefore, TFP index is a ratio of the weighted aggregate outputs to weighted aggregate inputs, using multiple outputs and inputs.

Input and output quantities of a group of firms are sets of data used to construct a piece-wise frontier over the data points. Efficiency measures are then calculated relative to this frontier that represents an efficient technology. The best-practice company determines the production frontier, that is, those that have the highest level of production given a level of economic inputs. Points that lie below the piece-wise frontier are considered inefficient while points that lie on or above the frontier are efficient.  

Since many inputs are used, and shared outputs may be produced, the Malmquist approach was developed to combine inputs and outputs and then measure changes. The Malmquist index measures the total factor productivity change (TFPCH), between two data points over time, by calculating the ratio of distances of each data points relative to a common technology.

Fare et al. (1994) specify the Malmquist productivity change index as:

        (1)

The above equation represents the productivity of the production point (xt+1,yt+1) relative to the production point (xt,yt). This index uses period t technology and the other period t+1 technology. TFP growth is the geometric mean of two output-based Malmquist-TFP indices from period t to period t+1. A value greater than one will indicate a positive TFP growth from period t to period t+1 while, a value lesser than one will indicate a decrease in TFP growth or performance relative to the previous year.  

The Malmquist index of total factor productivity change (TFPCH) is the product of technical efficiency change (EFFCH) and technological change (TECHCH) as expressed (Cabanda, 2001):

TFPCH = EFFCH x TECHCH                                  (2)

The Malmquist productivity change index, therefore, can be written as:

 = EFFCH x TECHCH                             (3)

Technical efficiency change (catch-up) measures the change in efficiency between current (t) and next (t+1) periods, while the technological change (innovation) captures the shift in frontier technology.

As expressed by Squires and Reid (2004), technological change (TECHCH) is the development of new products or the development of new technologies that allows methods of production to improve and results in the shifting upwards of the production frontier. More specifically, technological change includes both new production processes, called process innovation and the discovery of new products called product innovation.

With process innovation, firms figure out more efficient ways of making existing products allowing output to grow at a faster rate than economic inputs are growing. The cost of production declines over time with process innovations --new ways of making things.

Technical efficiency change, on the other hand, can make use of existing labor, capital, and other economic inputs to produce more of same product. An example is increase in skill or learning by doing. As producers gain experience at producing something they become more and more efficient at it. Labor find new ways of doing things so that relatively minor modifications to plant and procedures can contribute to higher levers of productivity.

Panel data allow for an estimation of technical progress (the movement of the frontier established by the best-practice firms) and changes in technical efficiencies over time (the distance of the inefficient firms from the best practice firm) or catching up.

This study uses three outputs and two inputs, which made it possible to run the output-orientated Malmquist DEA, using DEAP 2.1. The three outputs and two inputs were taken as measures of a firm's efficiency and productivity. The Philippine food manufacturing industry's outputs were: (a) total assets, (b) net sales; and (c) cost of goods sold.  Inputs were: (a) purchase cost; and (b) depreciation as proxy for capital. These outputs and inputs measures were calculated for the period 1997-2001, among a panel of 29 selected firms in our sample.  In aggregate, the test period covered about 145 years in the entire group of firms in the sample or industry that ensured a very rigorous and reliable result. The authors consider the time frame of four (4) years from 1997-2001 due insufficiency of data at this time. Data are only considered if they are continuously available. It is quite difficult to get financial data from SMEs, especially if these companies are not registered with the Securities and Exchange Commission.

Due to the small size of data sets, DEA method is more appropriate and suitable in this kind of analysis (Chu and Lim (1998)). Some other strengths of DEA are demonstrated by the following factors:

• The frontier approach does not require price information;
• It does not assume all firms are fully efficient or it allows inefficient performance;
• It does not need to assume a behavioral objective such as cost minimization or revenue maximization as typical of econometric approach;
• It permits TFP to be decomposed into technological change and technical efficiency change
• The addition of an extra firm in a DEA analysis cannot result in an increase in the TE scores of the existing firms;
• The addition of an extra input or output in a DEA model cannot result in a reduction in TE scores (Coelli (1998,p 181));
• It can manage multiple inputs and outputs; and
• Measurement error and statistical noise are assumed to be non-existent, thus accurate (see Mahadevan 2002:182)

IV. Empirical Results

Sources of TFP Growth

The results of the study reveal that the TFP growth of the Philippine food manufacturing industry (a group of firms in the sample) was due to EFFCH, with an index growth of 1.017 for the entire test period. Taken individually, the small and medium-sized firms' source of TFP growth was technological change, with index scores of 1.056 and 0.958, respectively. In contrast, the large-sized firms' TFP growth was mainly due to technical efficiency change, with an index growth of 1.013.

Table 1: Accumulated Malmquist productivity index of the Philoppine food manufacturing sector, 1997 - 2001

According to studies on productivity, in the case of developing countries, which borrow technology extensively from abroad, the lack of shifts in the frontier over time indicates the failure to innovate or develop new technology.

The Philippine food manufacturing industry (as reflected in our sample) has been good at moving towards the frontier or catching up. This result reveals that the growth in the food manufacturing industry was boosted by the enhancement of their productivity-based catching-up capability, specifically the effective use of human capital in the labor market and the adaption of the new technology. However, the result for technological growth points otherwise.

There has been deterioration in technological progress in the food manufacturing industry. Overall, there has not been a shift in the frontier in the Philippine food sector. This new result is consistent with Cororaton, et al.'s (1995) findings on TFP of the Philippine manufacturing industry that there has been a big gap or failure in technology advancement in terms of Research and Development and acquiring new technology, especially foreign technology.  This result, however, is in contrast to the findings of Liao and Holmes (2002), wherein, they found that the Philippine manufacturing industry exhibited some surges on technological frontier, but only in the later years did technical progress slightly improved. The study of Liao and Holmes however, is comprised of all manufacturing industries in the Philippines.

Cororaton et al. (1995) attributed technological progress to foreign direct investment (FDI), because FDI is a major vehicle for transferring foreign technology to the local economy. In short, low technological growth could be attributed to little technology transfer by the transnational corporations to the Philippines.

FDI, as a major vehicle for transferring technology, was also confirmed by the study of Mahadevan (2002) on Malaysia's TFP growth among 28 manufacturing industries.  Mahadevan (2002) revealed that the main source of TFP growth was technological change due to acquisitions of better technology and equipment via FDI.  This result is in contrast to the new finding in this study that the Philippine food industry suffered a declining technological growth over the time period.

It is interesting to note that only small-sized firms exhibited technological growth greater than one.  This means that small firms were able to cause shifts in their own frontier due to innovation. The new finding for small-sized firms' source of TFP growth is consistent with the findings of Rebelo et. al (2000) that small banks experienced higher technological change scores.

This new finding also affirms the results of a study conducted by the OECD (2001) that small firms are a source of constant renewal of technology and of technological breakthroughs. Small-sized firms are compelled to innovate and maintain their technological edge due to competitive pressures from their large incumbents. In fact, the so-called "new technology-based firms" are those small firms that play a crucial role in radical innovation and creation of new markets.

At some level, the lack of innovation causes businesses to decline and ultimately cease to operate. However, the type of innovation undertaken by these small and medium firms was no less difficult, though different, than that of large-powerhouse firms. The focus is often more on process than on product because process innovation often matters more than product innovation in terms of reducing costs and cycle time. The study of Dhawan (1999) likewise mentioned that small-sized firms have higher technological change than large-sized companies because they outperform large firms when it comes to their innovation rate, though, the bulk of R&D expenditures in the economy is undertaken by large firms. Their result is also affirmed by the new findings in this study.  Moreover, large firms may stay at the forefront of technology development for extended periods but, their leaderships are ultimately shaken by shifting technology and markets because of managerial or organizational sluggishness.

The same study also pointed out that the share of R&D performed by small and medium enterprises (SMEs) was generally higher in smaller economies than in large ones, this may be true with the Philippines as confirmed by this present study.

Although large-sized firms have low TECHCH, their EFFCH score was above one. The result shows that large-sized firms' source of TFP growth was technical efficiency or catching-up. This can be attributed to the advantages that large-sized firms enjoy, such as economies of scale, market power, and strategic grouping by firms.

This new result is consistent with the findings of Miller and Noulas (1994) that large banks have higher levels of technical efficiency.  This is, likewise, supported by the study of Dhawan (1999) that although small-sized firms are more innovative, they are riskier than their large counterparts. 

TFP Growth Changes

Small-sized Firms

There has been an improvement in the efficiency scores of small-sized firms relative to previous years, with 1.67 percent in period t+1, compared to �|4.41 percent in period t, with a growth change of -137.76 percent growth. TFPCH of small-sized firms has been declining from a high of 1.052 in 1998 to a low of 0.898 in 2001. There are four small-sized firms which have TFP indices equal to or above one; thus, 44 percent of the total small firms are performing well in terms of productivity.

Table 2: Distance Summary of Small-sized Firms

 

Table 3: Malmquist Index Summary of Firm Means for Small-sized Firms

Medium-sized Firms

The technical efficiency  (TE) scores of medium-sized firms shows a decline from periods t to t+1: -4.20 percent and �|7.01 percent, respectively. The Malmquist indices for medium-sized firms reveal that there have been variations in TFPCH for the whole test period. For the medium-sized firms, there are four firms out of ten (10) medium-sized firms whose TFP are above one for the entire test period. 

Table 4: Distances Summary of Medium-sized Firms

 

Table 5: Malmquist Index Summary of Firm Means for Medium-sized Firms

Large-sized Firms

Large-sized firms' Constant Return to Scale (TE) relative to technology declined between period t to period t+1, with growth changes of 1.52 percent and �|0.27 percent, respectively. There was a growth change of �|118.13 percent.  The results for large-sized firms reveal an increasing TFP rate from 1998 to 2001, though the TFP growth posted below one. Nevertheless, this result is encouraging for the large-sized firms.There are only three (3) out of ten (10) large-sized firms that are inefficient, so 70 percent of the firms had TFP scores equal to or above one.

Table 6: Distances Summary of Large-sized Firms

Table 7: Malmquist Index Summary of Firm Means of Large-sized Firms

Industry

The TE scores of the Philippine food industry improved over time largely from the current period (t) to the next period (t+1), with average growth rates of 0.56 percent and 2.53 percent, respectively. The change shows a remarkable growth as high as 350.43 percent.

There were variations in the TFP growth for the period 1998 to 2001.  It reveals that 13 out of 29 firms (45 percent) were efficient or had TFP growth equal or above one.  Out of these 13 firms, six (6) were from the large companies, two (2) from medium-sized firms, and five (5) from small-sized firms. Most of the firms' source of TFP growth was the technical efficiency change. A majority (65 percent) of the firms in our sample were technically efficient, whilst only seven (7) firms were technologically efficient.

Table 8: Distances Summary of the Philippine Food Industry

Table 9: Malmquist Index Summary of Firms Means of the Food Manufacturing Industry

V. Conclusions

Answers to the first research question are very important in the light of policy review or policy formulation. Findings show that the main source of TFP growth for the food manufacturing industry is technical efficiency change or catching-up.  This implies that the Philippine food manufacturing industry, as shown in the selected 29 firms in the sample, performs well over time as shown in its movement towards the frontier or catching-up. However, there is a deteriorating trend in technological progress over time, which implies that the Philippines has failed to develop and acquire or inject new technology from abroad over the test period.   FDI policies of the country should encourage or require foreign investors to inject new technology into the country to improve productivity. Another area that the Philippines can improve upon is in its Research and Development.

By classifying the Philippine food manufacturing industry in our sample into small, medium, and large-sized firms, the results showed that the sources of TFP growth differ among the firm sizes.  The main source of TFP growth for large-sized firms is technical efficiency change (EFFCH).   Large-sized firms showed the highest TFP growth, compared to small and medium-sized firms.  This new finding supports the predictions of many economic studies that large firms have more resources and have easy access to the global capital markets.  Small-sized and medium-sized firms, on the other hand, are more innovative, which contributed largely to its TFP growth.  Studies recognize the importance of SMEs in economic activity. Surprisingly, these firms are the source of constant renewal of technology and technological breakthroughs. 

Small firms typically lack market power and elaborate organization. They could only survive market uncertainties and capital constraints if they were technologically more efficient than their large counterparts. SMEs must continue to innovate in order to remain in the market, but they also face problems such as limited access to funds, markets, and skilled labors. These factors limit their innovation and adoption of new technologies.

There seems to be one general conclusion from the various studies on TFP conducted in the Philippines: TFP growth has not been improving. In fact, estimates, based on previous studies conducted, suggest negative TFP growths. The result of this study also indicates a decline in the TFP growth of the Philippine food manufacturing industry, but it is just a little below the efficient level (0.976).  A thorough analysis of the sources of TFP change is necessary in order to introduce remedies for productivity improvement. This is because TFP provides an indication of advances in technology and improvements in capital, labor, and market environment. 

Another significant finding of this study is the affirmation that a firm's size influences productivity and its sources of efficiency.   For individual firms, results of this study may also have firm-level policy implications. The efficiency results obtained by DEA yield values of inputs and outputs that a firm should be able to achieve. However, some factors that influence performance may not be under the control of the firms concerned.  DEA-Malmquist is limited only to input and output variables used to construct the model to estimate the changes of total factor productivity and to identify the sources of this TFP growth that will help in policy formulation for an industry.

The first task of a firm's management, after the DEA and the Malmquist indices results have been interpreted, is to examine the key characteristics of each frontier firm and then compare it to the inefficient firm(s) in the sample that may define the frontier. That way, they will be able to know which area they should improve upon.

This study provides some departure points for further research for policymakers as well as economic researchers.  As regards policy questions, the study explains in detail sources of TFP in the Philippine food manufacturing industry and the differences in relative efficiency and technological gains relative to firm sizes.  The result of the study shows that the Philippine food manufacturing industry is technologically inefficient; therefore, it lacks development and injection of new technology.  Another finding is that small-sized firms are technologically efficient as compared to large-sized firms, but they are more risky or technically inefficient.

The remaining issues to be resolved here are, to wit: What can the Philippines do to acquire or inject more new technology to the food manufacturing industry? What can the government do to help increase or encourage technical efficiencies of small-sized firms? These are important policy questions that should be addressed in a separate study involving future research.

The DEA-Malmquist method used for measuring TFP growth of the food manufacturing industry and the firms can be extended to a wider sample to give the DEA model a more discriminatory power, and its TFP decompositions (technical efficiency change and technological change) can also be given a wider coverage. The use of the DEA-Malmquist model in the Philippine food manufacturing industry to measure TFP will be a good departure point for future research as it has been for this study. A sensitivity analysis can be performed to establish relationships of TFP to firm age, leverage, and profitability, which are also acknowledged limitations of this present study.

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Footnotes

[1] Senior Trade and Industry Development Specialist,Department of Trade and Industry Sen. Gil Puyat Ave. Makati City, Philippines,Ph: (63-2) 890-9334; Fax: (63-2) 896-7889 Email: pamie1801@yahoo.com

[2] Emilyn C. Cabanda, Professor, Graduate School , University of Santo Tomas, Espana St., Manila Philippines; Ph: (63-2) 731-5396; Fax: (63-2) 740-9732; Email: eccabanda@mnl.ust.edu.ph

[3] We would like to acknowledge the financial support provided by the Graduate School of University of Santo Tomas in Manila, Philippines, especially to Dean Lilian Sison. The School provided also the financial assistance to present this study in the ASPAC 2004 Conference, held at the University of Oregon on June 18-19, 2004. Comments of anonymous referees are also gratefully acknowledged. Any errors remain are the responsibility of the authors only.