This paper bases on one of the seriously contested industrial topics: the functions of production and inputs in corporations. The study employed a triangulation method where data from various theoretical and empirical studies remained quite significant.
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Since there was no primary field data collected to validate the existing argument in the economic research about the relationship between productivity, this study opted to provide a general overview of the aspect of productivity in relation to inputs.
There was no case study included in this study, with several productivity types discussed comprehensively. It is important to understand that a profit organisation can produce through single-Factor Productivity or Multiple-Factor productivity, depending on the company’s objectives in the production paradigm.
Based on the theoretical evidence provided by several researchers, it is clear that inputs and outputs correlate, and their functions are inseparable. For any corporation to have a greater output, considerable energy must exist in the inputs to provide desirable production.
However, estimation of productivity is increasingly becoming a challenge to several economists with each of the methodologies having their merits and demerits accordingly. Cobb-Douglas production function has proven significant in estimating and calculating productivity growth with its ease in the application and flexibility remaining clear.
However, the design and specifications in Cobb-Douglas production function have allowed several researchers to rely on statistical data that rather than the underlying production function, thus resulting in poor estimations. Return to scale Technological progress has in the current state proven challenging, forcing the productivity approaches to include the time of production using technical support as a factor in estimating productivity.
However, based on several surveys on the empirical and theoretical literature on the microeconomic production function, Cobb-Douglas productions functions theory remains the most largely consumed method of production estimation.
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The world of globalisation and industrialisation has grown exponentially with the urge of increasing productivity and profit maximisation becoming more eminent in small, medium, and multinational corporations. In a bid to consolidate productivity and profit maximisation, companies have discovered several strategies to ensure proper achievement of their output targets.
One of the essentials in estimating production is the relationship between the productivity frights and the input levels. According to Petrin and Levinsohn (113), companies meant for profit maximisation normally respond to positive productivity shocks through output expansion, which in turn subsequently requires increased input.
Based on this positive correlation between the input and the production functions in a company, the two aspects remain paramount for all economics. However, research has indicated a lack of appropriate knowledge on the imperativeness of these factors, leading to downbeats and collapse of several corporations.
Alas, such knowledge remains misused or underutilised, leading to decreased productivity. For such reasons and more, this paper seeks to explore the functions of inputs and production.
Synopsis of variables
Production- Production in the industrial locale is a general term used to describe the techniques employed in manufacturing, fabrication, or invention of industrial goods, which are normally in the form of products or services. Productions in terms of producing goods in a firm typically refer to the means by which corporations use available raw material and integrate them into meaningful items of consumption or merchandise.
Syverson asserts, “Productivity is efficiency in production: how much output is obtainable from a given set of inputs” (329). Economists describe it simply as a means by which companies acquire output from its inputs. Production remains a fundamental aspect in all firms, including small, medium, and multinational corporations across all economies, including developed and developing.
Production is an essential component in company progress depending largely on other substantive factors including the amount and quality of input, quality of labour and workforce as well as physical capital. As postulated in industrial literature, all variable are equally significant in determining productivity.
Input- the term input refers to the all-contributing variables consumed in the production process to generate a product or service. Input being a key factor in production determines the quality of product or service generated.
Thus, firms are always keen on determining inputs suitable for a certain product in firms. According to Syverson (328), inputs are important variables for capacity utilisation in production where materials input measured in terms of monetary value, capital input and labour input/human capital measured in terms of competency workforce are essential input variables.
The quality of production may vary significantly from one organisation to another, depending on these input variables. Normally, the more stable the physical capital, human capital, and material input, the more efficient the production remains.
The two variables of profit maximisation and company growth directly correlate with each other and will remain inseparable as much as their definitions linger with appropriate meanings. Several researchers have identified the existing relationship between the variables scientifically.
Relationship between variables (inputs and outputs)
Following the growing concern to identify the factors attached to the growth of companies associated with the existing correlation between input factors and productivity concept, much scientific knowledge has emerged. According to Syverson (330), there are always possibilities of producers having quite different labour productivity levels, despite using similar production technology.
Because of such reasons, “researchers frequently use a productivity concept that is invariant to the intensity of use of observable factor inputs” (Syverson 330). To ascertain the relationship between input factors and the product concept, Total Factor Productivity (TFP), also known as multi-factor productivity, has been in regular use.
Syverson asserts, “TFP is most easily seen in the often-used formulation of a production function where output is the product of a function of observable inputs and a factor-neutral, shifter” (330). The equation Yt = At F (Kt, Lt, Mt), where Yt represents the output, F (.) is the function of observable capital Kt, labour Lt, and Mt as the material input.
Productivity growth and types of production
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Productivity is a measurable factor in an organisation where firms are capable of flourishing or collapsing depending on certain crucial factors. Productivity growth in itself refers to the basis in which corporations demonstrate improvement in terms of incomes and welfare.
Slow productivity usually “limits the actual rate in which incomes improve, thus affecting companies negatively as well as resulting in conflicting demands regarding the normal distribution of income” Wetmore 96). Productivity is a straightforward indicator in the general growth of businesses, where it depicts the relationship between inputs and outputs required to generate produce.
Therefore, “activities involved in measuring productivity growth and its related levels comprise important economic indicators” (Fox and Smeets 18).
For an organisation based on profit maximisation, the need to maintain a positive production curve that demonstrates consistent productivity growth is imperative to remain competitive in its market segment. However, productivity in a company may depend on several important input factors including labour force, machinery and technology and finance.
In a bid to understand properly how productivity in a company determines a company’s growth and development, it is essential to identify measures of productivity common in businesses. There exist “different productivity growth measures, with the choice between them depending upon the availability of data and the purpose of productivity measurement” (Saari 9).
There are three common subtypes of productivity based on the type and number of inputs employed. Productivity measure can fall under three classifications, namely partial (single-factor productivity), multi-factors productivity, and total-factors productivity.
Single-factor productivity “relates to an output measure resulting from a single measure of input, while multi-factor productivity measure refers to an output measure obtained from diverse inputs” (Wetmore 108).
Finally, total-factor productivity is a form of productivity, which refers to output measurement obtained from all input factors in a business. The following mathematical equations can be useful in explaining the information above as discovered by economic researchers.
In general, Productivity = output/input= average product or service.
Partial (Single-Factor Productivity) = Total Units Produced ÷ Labour Hours consumed
Multi-Factors Productivity= Total Output ÷ Labour + material + capital+ miscellaneous
Total Factors Productivity= Total Output ÷ Total Input
Production function with a single input
Production, typically in the form of either tangible product or service can be obtainable from a single input where only one productivity variable plays a crucial role in the entire process. Productivity, generally expressed as an output-input ratio must consider both variables for productivity to achieve a positive outcome.
A production that involves obtaining output from a single input refers to Single-factor productivity. Production using a single input simply refers to single-factor productivity in economics. Syverson postulates, “Single-factor productivity measures reflect units of output produced per unit of a particular input” (329).
In several cases of single-factor productivity, labour productivity is the most commonly applied as a means of measure of this type of productivity. In several occasions, the levels of single-factor productivity fall influence of intensive use of the excluded inputs.
According to Syverson (339), “attempts to capture labour quality differences in labour measures rather than productivity are the impetus behind using the wage bill to measure labour inputs rather than the number of employees or employee-hours.”
Labour or workforce forms part of single-factor productivity with employees determining the outcome of the productivity. Labour economists have continuously explored the importance of employees’ in the sense of human capital in elucidating productivity differences among companies and firms.
Employees are always great determiners of companies success, which many researchers define it through its power in productivity. Syverson postulates, “The notion is that market wages reflect variations in workers’ contributions to production; firms with more productive workers will have a higher wage bill per employee” (339).
In this context, the quality and quantity of the labour force in a company may affect the levels of productivity as one of the input factors related to the company’s productivity.
For several years, employers have affiliated several factors to labour quality, including levels of education, overall workers experience, levels of training and even permanent status with firms. Workers with greater working experience enhance positive productivity gain, as experience and other labour quality factors remain crucial.
Within the spirit of production theory, labour input for any industry remains the most appropriately measured in terms of an actual hour used in conducting jobs. The first modification of this employment measure is its “extension to total employment that comprises of estimation of inputs in the form of salaries and wages” (Wetmore 190).
The second refinement in this measurement includes “conversion from a simple job (or person) counts to estimates of total “hours actually worked” (Schreyer and Pilat 138).
Employees as inputs in single-factor productivity
Employees are essential input factors in the productivity of a firm, having the ability to influence the production in either a negative or positive manner. For companies to produce effectively, managers have found it imperative to consider the abilities of workers in their production.
This assertion explains the reason behind conduction performance appraisal and assessments in employees to determine their effectiveness and influence in the company’s progress. Employees’ performance is one of the single-factor productivity used in measuring productivity where, “for labour, there is the choice of whether to use the number of employees, employee-hours, or some quality-adjusted labour measure” (Syverson 331).
In developed economies like the U.S. economics within the manufacturing plants/firms data measure inputs as the value of the dollar in terms of physical capital and the number of workers existing in companies.
Companies have sometimes separated employees into productive and non-productive workers, which explain the reason why economists normally rely on calculating the wage bill instead of the number of workers in ascertaining human capital and physical capital.
Generally, human capital, as a single input factor in production, determines wages as the outcome of interest. Since it is difficult for economic researchers to use human capital measures to capture all aspects of worker quality due to the complicated nature of human ability, the majority have opted to use wage data in estimating the abilities of workers.
Normally, in all production factors, wages are proxies for worker labour quality in a competitive labour market. According to Fox and Smeets, “the wage bill is potentially a more accurate measure of input quality than the detailed human capital measures…indeed the wage bill specification usually gives less dispersion than the human capital specifications” (21).
Wages in this context reflect marginal product within a competitive labour market while estimating labour productivity as an input. Just as physical capital is measurable in monetary units, at least to create a partial reflection on the machinery quality employed, measuring labour expenses can be estimation terms to ascertain its quality.
Using wage bill instead of the number of employees as seen in the above explanation, therefore, provides a more significant technique in measuring human and physical capital. Employee’s details covering their productivity in any single company are always challenging to obtain from company sources, while data pertaining to employee wages and bills in terms of financial terms is easily accessible from company’s accounting datasets.
Obtaining detailed information about workers characteristics to determine labour quality has been a challenge to researchers, thus making the availability of this data irrelevant. The wage bill specification is quite significant in that the total amount of salaries and remunerations paid to workers in a company should reflect their productivity.
If the wage bill exceeds the production of a company that means the workforce, is becoming unproductive and managers, therefore, need to find remedial measures to avert the labour force/output leakages. Managers across corporations have always sought to employ a skilled workforce rather than unskilful labourers who end up consuming high wage bills with little or poor productivity.
Managers as inputs in single-factor productivity
Managers form an integral part in many profit-based corporations with their contribution more of an ideological asset than the workforce. Managers, like workers, form part of single-factor productivity, where the only variance in their expertise, skills, and experience proxies are most influential in measuring their productivity in organisations.
In short, there are no verities of managers or employees as in the case of raw material, machinery, and technology as main inputs to companies. Managers are essential employment inputs since their managerial competence can determine the overall productivity of a company, firm, or corporations.
Researchers have long associated personal managerial aspects found in managers to drive productivity differences among companies. Syverson affirms, “Managers are conductors of an input orchestra. They coordinate the application of labour, capital, and intermediate inputs” (336).
It is common, based on empirical evidence towards productivity in companies that deprived management normally leads to discordant production operations, just as poor conductors’ front to cacophony instead of the symphony.
Posing that managers form part of inputs towards productivity in companies may sometimes seem imaginary, as research has revealed many challenges in obtaining factual data on the manager’s appraisal to identify if they are a potential driver of productivity. Perhaps the most secretive wage bill information in companies is that concerning manager’s salaries, which many companies treat it as confidential compared to wage information regarding subordinates.
Syverson affirms, “The proliferation of micro-production data has afforded a great increase in detail, but such data rarely contains detailed information on any aspect of managerial inputs” (336). However, personal characteristics embedded in managers have great influence in determining productivity, with the manager’s talent or managerial talents, subsequently becoming essential factors of good management.
Managers are capable of determining and selecting for the company, type of technological machinery to utilise, the kind of workforce to employ as well as the market segments for company’s products or services, consequently affecting productivity.
Production function with multiple inputs
In the service and manufacturing industries, sometimes companies need to combine multiple sources to obtain an average product or service. A product or service can be obtainable from a variety of inputs as productivity factors.
Productivity function with multiple inputs refers to Multi-Factor Productivity (MFP), where all factors of production are equally important in determining the final product. Multi-Factor Productivity is also known as “total factor productivity, and economists often interpret its growth as one of the indicators of technological progress” (Wetmore 93).
Despite this scenario being seldom in actual productivity cases, Multi-Factor Productivity constantly suggests that all possible input factors are equally important. Multi-Factor Productivity contains an output involves.
According to Schreyer and Pilat affirm, “Another distinction, of particular relevance at the industry or firm-level, is between productivity measures that relate gross output to one or several inputs and those which use a value-added concept to capture movements of output” (128). This case can be in terms of capital, energy, labour, materials, and services.
Material as a factor to Multi-Factor Productivity
Productivity is measurable from several input factors, including financial capital, human capital, and even intermediate materials. For any company to generate a product, materials manufacturers refer to, as raw materials are essential.
In most cases, Multi-Factor Productivity is measurable in terms of gross output. According to Petrin and Levinsohn affirm, “Firms usually report positive use of intermediate inputs like electricity or materials, the quality of raw material influences the quality of output in the form of product or service achieved” (114).
According to prior research, Intermediate materials have been useful in examining productivity in companies in several ways since it is the most common input factor. Using intermediate input proxies in measuring productivity instead of permanent investment like machinery makes economics avoid shortening all the zero investment firms.
This aspect enables economic researchers to easily acquire pertaining productivity from a variety of companies making empirical evidence more accurate and reliable.
Intermediate materials have also shown huge significance in ascertaining productivity due to its data nature in which economists estimate the costs of materials purchased by companies for a certain output. Important data pertaining to the purchases of intermediate material as inputs in the productivity provides a broad and possible insight into the exact meaning of the use of material.
In a simpler explanation, several buy-sell companies, enterprises, or organisations based on profit maximisation depending on the input-output figures to calculate their gross profits. For economic researchers to obtain the value of output in terms Gross Value Added (VA), the proxy for this variable is obtainable by examining the existing difference between the value of finished goods and the expenditure incurred in purchasing intermediate material.
Materials as input in Multi-Factor productivity production can as well include important inputs like the raw material in the case of the manufacturing industry, packages, lubricants, electricity, and fuels that provide energy.
Labour as an input in Multi-Factor Productivity
Labour is an all-round productivity input with economic researchers using it as an essential input factor in the entire process. Labour is among the primary factors of production in the bracket of capital and land, which have remain independent determinants of production in economics, as discussed in several theoretical and empirical studies.
Economists normally calculate the actual human capital using time and wage/salary spent in paying the workers for their contribution towards production at a certain level. Labour efficacy can greatly determine the productivity of a given corporation in the sense that productive workers provide room for increased productivity, while unskilled and lazy workers are unproductive, consequently leading to varied performances among companies.
From the right definition, that distinguishes types of production functions, Multi-factor productivity means the inclusion of several production inputs to obtain an average output in the form of product or service. According to Syverson (352), employees are the most independent inputs in any given organisation, since they determine the flexibility of production based on the human nature and power to drive and operate other production inputs.
Return to scale Technological progress
Based on several economic research, the assumptions of Constants Return to Scale (CRS) and perfect competition has increasingly proven imminent, thus, it has become essential to give exceptional while determining the productivity growth of corporations.
With this element in place, it has become relatively easier to calculate estimates associating with the impact of technological changes using several techniques. To avoid extensive assumptions while determining the productivity growth of companies, Constant Return to Scale (CRS) evidence has come clearly important for assessing the importance of theoretical macroeconomic and microeconomic.
Research has identified a great variance in companies using the technological approach from those using traditional approaches in their production. As the need to integrate new-sophisticated technologies, the productivity within companies is increasingly differing from a range of companies. Technology can be a Constants Return to Scale (CRS) factor where time factor remains a significant issue in the determination of productivity parity in organisations.
Many economists have affiliated the need of growing technology with positive changes within the productivity circles of corporations. Thus, changes in the calculation of productivity growth become eminent.
As discussed in the Cobb-Douglas production function where consideration of production time is essential to provide a clear-cut distinction between the technically supported corporations and the traditionally manual operated corporations, similar findings are inherent in assessing Constant Return to Scale (CRS) Technological aspect.
Economists assume that technologically supported corporations yield higher compared to manual work completed by a single man per production. According to research, there is a considerable increase in labour output using machinery determined by the relative importance of intensive capitalisation and the technical progress in the increasing output per single worker.
As compared to the simple functions of estimating productivity, the equation Y= A (t) F (K, L), where Y, K and L are homogenous variables, while A (t) represents time in the aspect of technological progress. Generally, Syverson affirms, “researchers can use a multiplicatively separable technology shift to make exposition easy, but TFP can be extractable from a general time-varying production function” (330); its formula is as follows:
Yt =G t (At, Kt, Lt, Mt)
Cobb-Douglas Production Functions
One of the most acknowledged approaches in the mechanisms of studying productivity economics rests upon the theoretical approaches of Cobb-Douglas production functions. The Cobb- Douglas production function measure is a simple production function that economists deliberate it with a reasonable explanation of definite economies.
The Cobb-Douglas production function emerged from works of labour economist Paul H. Douglas and the great mathematician Charles W. Cobb. The Cobb-Douglas technique of measuring production function measure resulted in a proposition to authenticate Douglas’s empirical results for production inputs, including capital stock and employment way back in 1928 in the U.S. manufacturing industries.
Due to its easiness and simplicity in its application with greater flexibility compared to other methods, economists have continuously preferred using this functional form to analyse organisational productivity.
Douglas and Charles provided the instrumental approach that has consistently received global fame by economic researchers, thus remaining quite imperative. The Cobb-Douglas production function, subsequently employed in economic research, can take the following form:
Y= A Lβ1Kβ2 or Y = AK α L1-α
In this first equation, Y represents the output, whereas K represents the capital input, L represents labour, α is a constant that represents a value between zero and the minimal 1. Finally, A is the level of technology (A≥ 0). On the second equation, Q, L, and K represent output, labour, and capital, respectively, while β1 and β2 are constants in this equation.
Economists assume that constant returns to scale with β1 and β2 results to 1. Fraser affirms that in estimating production, “by imposing CRS, it is only necessary to estimate β1, effectively avoiding any potential problem of co-linearity in estimation” (41).
A Cobb-Douglas production function uses different means estimation with different economic metric methods inclusive of the famous and reliable General Methods of Moments (GMM). GMM estimator is a generic method used in estimating parameters in arithmetical representations.
The GMM estimator is one of the main determinants of Multi-Factor Productivity intended for identifying econometrically, possible determinants of productivity or output growth.
General Methods of Moments (GMM) is an estimator factor that has been useful and Cobb–Douglas production asymmetric style is the approach that is probably the most common in the literature. Cobb-Douglas, with respect to manufacturing, uses a difference GMM estimator, which presents a constant return (CRS) scale.
A significant issue to consider in Cobb-Douglas production function is that the imposition of CRS restriction without justifying is econometrically substandard. Cobb- Douglas tried to relax without considering any impact on the estimated values of β1 and β2. A problem noted in the use of Cobb-Douglas production function is clear with respect to the original specification of the relationship between the functional omissions of the technical change.
“Unless it is possible to assume that there existed technical or technological data over the entire production period, thus A remains as constant” (Wetmore 141). When this scenario occurs, researchers conclude that there is a need to re-estimate the produced data to ascertain productivity with supplementary descriptive variables. Fraser asserts, “A standard procedure for introducing the possibility of technical change is to include a time trend (T)” (41) bearing the following equation:
Q=A (t) Lβ1 Bβ2
This equation provides a room for economic researchers to include the probability of including technological support in estimating productivity in companies. Technology has emerged competent and more efficient in production and therefore, time consumed in matters when production involves technology. To provide a slight description of the above equation, A (t) = A e ά. A and ά are usually constant.
In this equation, ά is the measure of the appropriate change exhibited in output per period when the input levels remain constant. In simple terms, the impartial change in Q, which is the output, happens due to the technical progress employed from the technological aspect employed in the company.
Fraser postulates, “This specification incorporates neutral technical change- there is no impact on the marginal rate of substitution between capital and labour” (41). Through such an explanation, it is possible to identify that the technological input variable as an aspect to the productivity paradigm is exogenous.
Advantages of Cobb-Douglas productions functions theory
Based on several surveys on the empirical and theoretical literature on the microeconomic production function, Cobb-Douglas productions functions theory remains the most largely consumed method of production estimation. Cobb-Douglas production function based on mathematical and scientific approaches combined to provide absolute method desirable for estimating productivity has proven significant in economic studies for decades.
According to several economic research based on industrial productivity, Cobb-Douglas have been more efficient in the sense that it bears to strengths in its ease in the application, with the good empirical fit across many data sets.
In all sets of productivity calculation meant to identify the production levels of companies, Cobb-Douglas production function has provided room for economists to ascertain the productivity of corporations where there has been a violation of fundamental assumptions occurs.
The easiness in the application of the Cobb-Douglas production function allows economic researchers to validate through all data sets and compose reliable reports on the productivity of these corporations. All business corporations are capable of use using Cobb-Douglas production approach.
An important consideration of sophisticated mechanical technologies has become essential in all companies, with productivity largely depending on the integration of technological devices within corporations. Based on the Cobb-Douglas production function, one of the paramount productivity inputs to consider is technical support, with this function stressing that all input factors are equally significant.
The diverse application of mechanical support systems across companies has become eminent in the current world of industrialisation, where Cobb-Douglas production function has continued to prove imperative. Cobb-Douglas production function argues that all input factors are paramount and technology being amongst them remains central.
Following studies conducted by Fraser (41) based on Cobb-Douglas production function; time (T) is the most important aspect to consider while considering technical support in production.
Companies using technological support have affiliated with greater, time-efficient and effective production across corporations and therefore remains fundamental in calculating productivity. Based on this aspect, Douglas specification remains imperative in ascertaining productivity in the current technologically supported macro and micro corporations.
Cobb-Douglas production function rests upon the metrics of the Generalised Method of Moments (GMM) in estimating parameters of statistical data, which has been the most accepted estimator in productivity. GMM has been a dynamic estimation approach that enables the inclusion of several production inputs to examine the productivity function in organisations.
GMM allows the inclusion of miscellaneous inputs inclusive of likely endo-geniality of some regressors, dependent input variables and the possibility of omitting fundamental variables. With this insight in mind, the GMM estimator econometric method remains an essential consideration in Cobb- Douglas production function.
It normally allows robustness to the results of the production function with such results appealing strongly in the empirical proof.
GMM methodology has been crucial with important inclusion of proxies such labour, capital and knowledge as inputs in this methodology, which proves that Cobb- Douglas based on GMM methodology results in unbiased and efficient estimators of ascertaining production function parameters. This fact explains the dynamics in the application of GMM methodology.
Disadvantages of Cobb-Douglas productions functions theory
Despite having several significances in determining the productivity parameters in companies, several researchers have criticised Cobb-Douglas production function in some aspects of its application.
According to Fraser (39), Cobb Douglas production function emerged due to the urge to replace economic theorist’s works after reaching a conclusion that these theoretical perspectives rarely illustrated appropriate marginal productivity curves, but continuously provided assumptions.
Cobb-Douglas is an extensive production methodology that allows the inclusion of diverse production inputs, considering each individual input is paramount. This element normally allows various extensions to the original estimation data.
In the process of ascertaining the productivity of miscellaneous inputs, the results might remain unclear in the sense that these inputs are extraneous in providing perfect productivity growth.
Data obtained from miscellaneous is highly inconsistent since companies estimate most of this data, which may result from figures recorded in an indecent manner. Sometimes converting miscellaneous data into values and units that economists can mathematically prove is challenging, making the Cobb-Douglas’s inclusion of diverse inputs insignificant.
The design and specifications in Cobb-Douglas production function have allowed several researchers to rely on statistical data that rather than the underlying production function. Researchers have been undertaking their studies using statistical artefact in determining productivity in companies, thus providing aggregate production functions.
In real economies, aggregate production functions heavily rely on the use of factor elasticity and marginal products, which are macroeconomic concepts, whereby macroeconomics manipulates to simplify their models.
Despite the fact that estimating capital and labour parameters in the entire economies of macroeconomic corporations is a common practice, it is evident that these measurement associated with an economically meaningful relationship. In several applications of Cobb-Douglas production function, data from many variables are from a span of time, thus failing to provide current parameters associated with productivity at recent times.
This aspect refrains from the practical relationship that productivity and organisations need to enhance production progressively. Therefore, the Cobb-Douglas production function allows room for manipulated empirical evidence.
As postulated before, most of the methodologies used in the Cobb-Douglas production function use marginal revenue products, which have no definite calculating figures. The elasticity aspect in the Cobb-Douglas production function triggered by the inclusion of marginal revenues products of capital or labour inputs remains unanticipated, resulting in distortions in production data.
Syverson posits, “Marginal revenue products are equated across all uses and the fact that marginal products are proportional to average products for a Cobb–Douglas production function without fixed costs” (356). In several occasions, estimations in the marginal products result in unclear results since the independent user cost do not accurately produce the real units for calculating productivity.
As user costs reflect the marginal productivity of different assets in equilibrium condition and in the competitive markets, this aspect does not provide effective data to incorporate differences in the prolific contribution of assorted investments as such investments change with time. These yields invalid data on the productivity of a company.
Several studies have tried concurrently over the years to determine the most suitable means of estimating or calculating the productivity growth. As the literature for economics in the productivity of companies enhance, the need to determine more efficient and effective means of estimating and ascertaining the productivity growth is paramount.
Syverson asserts, “Several studies have tried to measure the rate of capital-embodied technological progress by carefully constructing measures of the distribution of capital vintages within plants or firms” (340). However, the measure of technological progress that determines the competence of companies in productivity remains unclear.
Estimating time consumed in the production of either a good or a product in industry has always remained a challenge with the aspect of time being clearer when estimating workers individual time rather than machinery. The fact being that most data obtained from the industries is usually unsupported to provide concrete support to the empirical evidence produced by economic researchers.
Production function in any given profit-based organisation is an imperative factor and the need to ascertain its growth is another. Companies have found it necessary to consider all aspects associating empirical economic research to examine their overall progress.
Based on the theoretical evidence provided by several researchers, it is clear that inputs and outputs correlate, and their functions are inseparable. For any corporation to have a greater output, considerable energy must exist in the inputs to provide desirable production. However, estimation of productivity is increasingly becoming a challenge to several economists with each of the methodologies having their merits and demerits accordingly.
Some methodological approaches appeared before the augmented technological aspect became eminent in the traditional era, thus making unnecessary in their application in the recent industrial epoch. This study, therefore finds it imperative for economists to identify possible production estimating methodologies to ease the economics research and enhance the validity in empirical evidence provided.
Fox, Jeremy, and Valerie Smeets. Does Input Quality Drive Measured Differences in Firm Productivity, 2010.
Fraser, Ian. “The Cobb-Douglas Production Function: An Antipodean Defence?” Economic Issues 7.1 (2002): 39-58. Print.
Petrin, Amil, and James Levinsohn. “Production function estimation in Stata using inputs to control for unobservables.” The Stata Journal 4.2 (2004): 113–123. Print.
Saari, Seppo 2006, Productivity. Theory and Measurement in Business. Productivity Handbook. PDF file.
Schreyer, Paul, and Dirk Pilat 2001, Measuring Productivity. PDF file.
Syverson, Chad. “What Determines Productivity?” Journal of Economic Literature 49:2(2011): 326–365. Print.
Wetmore, Donald. The Productivity Handbook: New ways of leveraging your time, information, and communications, New York: Random House, 2007. Print.