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Managerial Economics – Analysis, Problems and Cases, P.L. Mehta, Sultan Chand Managerial Economics – Varshney and Maheshwari, Sultan Chand and. Assignment on managerial economics varshney and maheshwari. Napoleon bonaparte essay biography physical education assignments teks supply chain. decision making - Role of Managerial Economist - Fundamental concepts of R.L. Varshney, K.L. Maheshwari, Managerial Economics, Sultan Chand & Sons.

Zulull Managerial economics varshney maheshwari You can also drop in a mail at cs sapnaonline. I look for a PDF Ebook managerial economics by varshney and maheshwari. Economics is managerial economics by varshney and maheshwari study of how to best allocate scarce resources among competing uses. Principles and Practice mzheshwari Management. Books for Professional Courses Shop with an easy mind and be rest assured that your online shopping experience with SapnaOnline will be the best at all times. Firms exist because they are useful in the process of allocating resources —producing and distributing goods and services.

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I look for a PDF Ebook managerial economics by varshney and maheshwari. Economics is managerial economics by varshney and maheshwari study of how to best allocate scarce resources among competing uses. Principles and Practice mzheshwari Management. Books for Professional Courses Shop with an easy mind and be rest assured that your online shopping experience with SapnaOnline will be the best at all times.

Firms exist because they are useful in the process of allocating resources —producing and distributing goods and services. It helps in decision making regarding sales, production, and profit. Managerial economics maheshwari We will in fact show the transition from the sale force as outside agents to download to the sale force Cris Lewis, Managerial Economics, 4th Edition Submit Review Submit Review. Therefore it is necessary to study how wealth is produced. Managerial economics is a science that deals with the application of various economics theories, principles, concepts and techniques to business management in order to solve business and management problems It deals with the practical application of economic theory and methodology to decision-making problems managerial economics by varshney and maheshwari by private, public and non profit making organizations.

The structure of systems to evaluate the performance of individuals and units Managerial economics by varshney and maheshwari three components are often referred to a stool with three legs.

Manufacturing schedules can be drafted in compliance with the demand requisites; in this manner cutting down on the inventory, production and other related costs.

Demand forecasting furthermore smoothes the process of evaluating the efficiency of the sales department. Quality and Quantity Controls: Demand forecasting is an essential and valuable instrument in the control of the management of an organisation to provide finished goods of correct quality and quantity at the correct time with the least amount of expenditure.

Financial Estimates: As per the sales level as well as production functions, the financial requirements of an organisation can be calculated using various techniques of demand forecasting. In addition, it needs a little time to acquire revenue on practical terms. Sales forecasts will, as a result, make it possible for arranging adequate resources on practical terms and in advance as well.

Avoiding Surplus and Inadequate Production: Demand forecasting is necessary for the old and new organisations. It is somewhat essential if an organisation is engaged in large scale production of goods and the development period is extremely time-consuming in the course of production. In such situations, an estimate regarding the future demand is essential to avoid inadequate and surplus production. Recommendations for the future: Demand forecast for a specific commodity furthermore provides recommendations for demand forecast of associated industries.

Significance for the government: At the macro-level, demand forecasting is valuable to the government as it aids in determining targets of imports as well as exports for various products and preparing for the international business.

Collective forecasts develop precision and decrease the probability of huge mistakes. Methods that relay on Qualitative Assessment: Forecasting demand based on expert opinion. Some of the types in this method are: Methods that rely on quantitative data: Prediction markets: These are speculative markets fashioned with the intention of making predictions. Assets that are produced possess an ultimate cash worth bound to a specific event e. The present market prices can then be described as forecasts of the likelihood of the event or the estimated value of the situation.

Prediction markets are as a result planned as betting exchanges, without any kind of compromise for the bookmaker. People who download low and sell high are rewarded for improving the market prediction, while those who download high and sell low are punished for degrading the market prediction. Evidence so far suggests that prediction markets are at least as accurate as other institutions predicting the same events with a similar pool of participants.

Many prediction markets are open to the public. Intrade is a for-profit company with a large variety of contracts not including sports. Trade Sports are prediction markets for sporting events. Delphi method: This is a systematic, interactive forecasting method which relies on a panel of experts. The experts answer questionnaires in two or more rounds. Thus, experts are encouraged to revise their earlier answers in light of the replies of other members of their panel.

It is believed that during this process the range of the answers will decrease and the group will converge towards the 'correct' answer. Finally, the process is stopped after a pre-defined stop criterion e. Game theory: Game theory is a branch of applied mathematics that is used in the social sciences, most notably in economics, as well as in biology particularly evolutionary biology and ecology , engineering, political science, international relations, computer science and philosophy.

Game theory attempts at mathematically capturing behaviour in strategic situations or games in which an individual's success in making choices depends on the choices of others. Today, "game theory is a sort of umbrella or 'unified field' theory for the rational side of social science, where 'social' is interpreted broadly, to include human as well as non- human players computers, animals, plants " Aumann Traditional applications of game theory aim at finding equilibrium in these games.

In equilibrium, each player of the game has adopted a strategy that they are unlikely to change. Many equilibrium concepts have been developed most famously the Nash equilibrium in an endeavor to capture this idea. These equilibrium concepts are differently motivated depending on the field of application, although they often overlap or coincide. This methodology is not without criticism and debates continue over the appropriateness of particular equilibrium concepts, the appropriateness of equilibrium altogether and the usefulness of mathematical models more generally.

This theory was developed extensively in the s by many scholars. Game theory was later explicitly applied to biology in the s, although similar developments go back at least as far as the s.

Game theory has been widely recognised as an important tool in many fields. The games studied in game theory are well-defined mathematical objects. A game consists of a set of players, a set of moves or strategies available to those players and a specification of payoffs for each combination of strategies. Most cooperative games are presented in the characteristic function form, while the extensive and the normal forms are used to define non-cooperative games.

Discrete-event simulation: The operation of a system is represented as a chronological sequence of events. Each event occurs at an instant in time and marks a change of state in the system. For example, if an elevator is simulated, an event could be "level 6 button pressed", with the resulting system state of "lift moving" and eventually unless one chooses to simulate the failure of the lift "lift at level 6".

A common exercise in learning how to build discrete-event simulations is to model a queue, such as customers arriving at a bank to be served by a teller. Rule based forecasting: Rule-based forecasting RBF is a proficient method that incorporates judgment as well as statistical techniques to merge forecasts.

It involves condition-action statements rules where conditions are based on the aspects of the past progress and upon knowledge of that specific area. These rules give in to the load suitable to the forecasting condition as described by the circumstances. In fact, RBF uses structured judgment as well as statistical analysis to modify predictive techniques to the condition. Practical outcomes on several sets of the past progress indicate that RBF generates forecasts that are more precise than those generated by the conventional predictive techniques or by an equal-load amalgamation of predictions.

Data mining: Data mining is the process of extracting patterns from data. Data mining is seen as an increasingly important tool by modern business to transform data into an informational advantage.

It is currently used in a wide range of profiling practices, such as marketing, surveillance and scientific discovery. Data mining commonly involves four classes of tasks: For example, an email program might attempt to classify an email as legitimate or spam.

Common algorithms include decision tree learning, nearest neighbor, naive Bayesian classification, neural networks and support vector machines. For example a supermarket might gather data on customer downloading habits. Using association rule learning, the supermarket can determine which products are frequently bought together and use this information for marketing purposes.

This is sometimes referred to as market basket analysis. Regression analysis: Regression analysis is the statistical technique that identifies the relationship between two or more quantitative variables: The technique is used to find the equation that represents the relationship between the variables. The steps in regression analysis are: Construction of the causal model: The construction of an explanatory model is a crucial step in the regression analysis.

It must be defined with reference to the action theory of the intervention. It is likely that several kinds of variable exist. In some cases, they may be specially created, for example to take account of the fact that an individual has benefited from support or not a dummy variable, taking values 0 or 1.

A variable may also represent an observable characteristic having a job or not or an unobservable one probability of having a job. The model may presume that a particular variable evolves in a linear, logarithmic, exponential or other way. All the explanatory models are constructed on the basis of a model, such as the following, for linear regression: For example, when questioning women about unemployment, if they have experienced periods of previous unemployment which are systematically longer than those of men, it will not be possible to separate the influence of the two explanatory factors: Construction of a sample: To apply multiple regression, a large sample is usually required ideally between 2, to 15, individuals.

Note that for time series data, much less is needed. Data collection: Reliable data must be collected, either from a monitoring system, from a questionnaire survey or from a combination of both. Calculation of coefficients: Coefficients can be calculated relatively easily, using statistical software that is both affordable and accessible to PC users.

Test of the model: The model aims to explain as much of the variability of the observed changes as possible.

To check how useful a linear regression equation is, tests can be performed on the square of the correlation coefficient r. This tells us what percentage of the variability in the y variable can be explained by the x variable. A correlation coefficient of 0. Thus, the smaller the residue better is the quality of the model and its adjustment.

The analysis of residues is a very important step: It is the residue analysis that also enables one to tell whether the tool has made it possible to estimate the effects in a plausible way or not. If significant anomalies are detected, the regression model should not be used to estimate effects and the original causal model should be re-examined, to see if further predictive variables can be introduced.

Time series analysis: An analysis of the relationship between variables over a period of time. Time-series analysis is useful in assessing how an economic or other variable changes over time. For example, one may conduct a time-series analysis on a stock, sales volumes, interest rates and quality measurements etc. Methods for time series analyses may be divided into two classes: Frequency domain: Frequency domain is a term used to describe the domain for analysis of mathematical functions or signals with respect to frequency, rather than time.

A time-domain graph shows how a signal changes over time. Whereas a frequency-domain graph shows how much of the signal lies within each given frequency band over a range of frequencies. Time domain: Time domain is a term used to describe the analysis of mathematical functions, or physical signals, with respect to time.

In the time domain, the signal or function's value is known for all real numbers, for the case of continuous time, or at various separate instants in the case of discrete time.

An oscilloscope is a tool commonly used to visualise real-world signals in the time domain. Utility analysis: A subset of consumer demand theory that analysis consumer behavior and market demand using total utility and marginal utility.

The key principle of utility analysis is the law of diminishing marginal utility, which offers an explanation for the law of demand and the negative slope of the demand curve. The main focus of utility analysis is on the fulfillment of wants and needs acquired by the utilization of goods. It additionally facilitates in getting the knowledge of market demand as well as the law of demand.

The law of demand by way of utility analysis states that consumers download goods that fulfill their wants and needs, i. Those goods that create more utility are more important to consumers and therefore downloaders are prepared to pay a higher price.

The main aspect to the law of demand is that the utility created falls when the quantity consumed rises. As such, the demand price that downloaders are prepared to pay falls when the quantity demanded rises. The law of diminishing marginal utility asserts that marginal utility or the extra utility acquired from consuming a good, falls as the quantity consumed rises.

Basically, each extra good consumed is less fulfilling as compared to the previous one. This law is mostly significant for awareness into market demand as well as the law of demand.

Cardinal utility: A measure of utility, or satisfaction derived from the consumption of goods and services that can be measured using an absolute scale. Cardinal utility exists if the utility derived from consumption is measurable in the same way that other physical characteristics--height and weight--are measured using a scale that is comparable between people.

There is little or no evidence to suggest that such measurement is possible and is not even needed for modern consumer demand theory and indifference curve analysis. Cardinal utility, however, is often employed as a convenient teaching device for discussing such concepts as marginal utility and utility maximisation.

Ordinal utility: A method of analysing utility, or satisfaction derived from the consumption of goods and services, based on a relative ranking of the goods and services consumed. With ordinal utility, goods are only ranked only in terms of more or less preferred, there is no attempt to determine how much more one good is preferred to another. Ordinal utility is the underlying assumption used in the analysis of indifference curves and should be compared with cardinal utility, which hypothetically measures utility using a quantitative scale.

Study Notes Assessment Write notes on the following: Objectives of Demand Forecast 2. Importance of Demand Forecast 3. Methods of Demand Forecast 4. Regression analysis 5. Cardinal utility 6.

Law of Demand: The Law of demand thus merely states that the price and demand of a commodity are inversely related, provided all other things remain unchanged or as economists put it ceteris paribus.

Assumptions to the Law of Demand: Why Demand Curve Slopes Downwards: The reasons behind the law of demand, i. Market Demand: Individual demand: The individual demand means the quantity of a product that an individual can download given its price.

It implies that the individual has the ability and willingness to pay. Demand Function: Demand function is a mathematical expression of the law of demand in quantitative terms.

A demand function may produce a linear or curvilinear demand curve depending on the nature of relationship between the price and quantity demanded. The concept of elasticity of demand can be defined as the degree of responsiveness of demand to given change in price of the commodity.

Methods of Measurement of Elasticity of Demand: By using three different methods, elasticity of demand is measured. Objectives of Demand Forecast: Following are the objectives of demand forecasting: It attempts to capture behaviour mathematically in strategic situations or games in which an individual's success in making choices depends on the choices of others.

While initially developed to analyse competitions in which one individual does better at another's expense zero sum games , it has been expanded to include a wide class of interactions, which are classified according to several criteria. State the law of demand and show it through a demand schedule and a demand curve.

What are the exceptions to the law of demand? Explain the concepts of arc and point elasticity of the demand curve for a commodity. What is the problem in using the arc elasticity? How can this problem be resolved? How is the point elasticity on curvilinear demand curve measured? Prove the following: Two parallel straight-line demand curves have different price elasticity at the same price.

Two intersecting straight-line demand curves have different elasticity at the point of intersection. Short Questions a. Demand Forecasting b. Law of Demand c. Increase and decrease in demand d. Importance of Demand Forecasting e. Methods of measuring Elasticity of Demand f.

Demand Forecast and Sales Forecast g. Prediction markets h. Delphi method i. Game theory j. Regression analysis k. Time series analysis l. Cardinal utility m. Suppose a demand schedule is given as follows: Work out the elasticity for the fall in price from Rs 80 to Rs Calculate the elasticity for the increase in the price from Rs 60 to Rs Why is the elasticity coefficient in a different form that in b?

Business Economics, Adhikary, M,. Managerial Economics, Chopra, O P. Managerial Economics, Varshney, R L. Which of the following statements are right or wrong?

The coefficient of the price-elasticity of a demand curve between any two points remains the same irrespective of whether price falls or rises. The slope of a demand curve gives the measure of its elasticity. Two parallel straight-line demand curves have the same elasticity at a given price. Two intersecting straight-line demand curves have the same elasticity at the point of their intersection. Two straight line demand curves originating at the same point on the price axis have the same elasticity at a given price, h.

When income increases, the expenditure on essential goods increases more than proportionately i. The demand for a product increases when price of its substitute increases, j.

The greater the cross elasticity, the closer the substitute, k. The price elasticity of the supply of a commodity is always negative. The income elasticity of the demand for luxury goods is always positive, m. If price elasticity is less than one and price rises, the total expenditure decreases, n.

If price elasticity is equal to one, the total revenue increases with the increase in price [Ans. Right Statements— g , i , j , k ] 2. Which of the following gives the measures of price elasticity of demand? The ratio of change in demand to the change in price b.

The ratio of change in price to the change in demand c. Which of the following gives the measure of price elasticity of demand?

Price of a commodity falls and its demand increases so that elasticity is estimated to be 1. Suppose price increases back to its old level. Will price elasticity be a the same b less than 1. At a given price, two parallel demand curves have a.

The same point elasticity b. Different point elasticity 6. Two intersecting demand curves have at the point of their intersection a the same elasticity b a different elasticity 7. A less-than-zero income elasticity indicates that with an increase in income, consumption of a product a Turns negative b increase b Decrease d remains constant? It is a continuous process Content Map 3.

A production function is a mathematical relationship that captures the essential features of the technology by means of which an organisation metamorphoses resources such as land, labour and capital into goods or services such as steel or cement. Mathematically, let Y denote the quantity of a single output produced by the quantities of inputs denoted x1, Then the production function f x1, Several important features of the structure of the technology are captured by the shape of the production function.

Relationships among inputs include the degree of substitutability or complementarily among pairs of inputs, as well as the ability to aggregate groups of inputs into a shorter list of input aggregates. Relationships between output and the inputs include economies of scale and the technical efficiency with which inputs are utilised to produce a given output.

Each of these features has implications for the shape of the cost function, which is intimately related to the production function. A cost function is also a mathematical relationship, one that relates the expenses an organisation incurs on the quantity of output it produces and to the unit prices it pays. Mathematically, let E denote the expense an organisation incurs in the production of output quantity Y when it pays unit prices p1, Then the cost function C y, p1, A cost function is an increasing function of y, p1, For example, scale economies enable output to expand faster than input usage.

In other words, proportionate increase in output is larger than the proportionate increase in inputs. Such a situation is also denoted as elasticity of production in relation to inputs being grater than one scale economies thus create an incentive for large-scale production and by analogous reasoning scale diseconomies create a technological deterrent to large-scale production.

For another example, if a pair of inputs is a close substitute and the unit price of one of the inputs increases, the resulting increase in cost is less than if the two inputs were poor substitutes or complements. As these examples suggest, under fairly general conditions the shape of the cost function is a mirror image of the shape of the production function. Thus, the cost function and the production function generally afford equivalent information concerning the structure of production technology.

Such a duality relationship has a number of important implications. Since the production function and the cost function are based on different data, duality enables us to employ either function as the basis of an economic analysis of production, without fear of obtaining conflicting inferences. The theoretical properties of associated output supply and input demand equations may be inferred from either the theoretical properties of the production function or, more easily, for those of the dual cost function.

Empirical analysis aimed at investigating the nature of scale economies, the degree of input substitutability or complementarily, or the extent and nature of productive inefficiency can be conducted using a production function or again more easily using a cost function.

If the time period under consideration is sufficiently short, then the assumption of a given technology is valid. The longer-term effects of technological progress or the adaptation of existing superior technology can be introduced into the analysis. Technical progress increases the maximum output that can be obtained from a given collection of inputs and so in the presence of unchanging unit prices of the inputs technical progress reduces the minimum cost that must be incurred to produce a given quantity of output.

This phenomenon is merely an extension to the time dimension of the duality relationship that links production functions and cost functions. Of particular empirical interest are the magnitude of technical progress and its cost-reducing effects and the possible labour-saving bias of technological progress and its employment effects that are transmitted from the production function, to the cost function and then to the labour demand function.

A production function can be an equation, table or graph presenting the maximum amount of a commodity that a firm can produce from a given set of inputs during a period of time. More specifically, it shows the maximum volume of physical output available from a given set of inputs or the minimum set of inputs necessary to produce any given level of output. The production function comprises an engineering or technical relation, because the relation between inputs and outputs is a technical one.

The production function is determined by a given state of technology. When the technology improves the production function changes, because the new production function can yield greater output from the given inputs or smaller inputs will be enough to produce a given level of output. Further, the production function incorporates the idea of efficiency. Thus, production function is not any relation between inputs and outputs, but a relation in which a given set of inputs produces a maximum output.

Therefore, the production function includes all the technically efficient methods of producing an output. A method or process of production is a combination of inputs required for the production of output. A method of production is technically efficient to any other method if it uses less of at least one factor and no more of the other factors as compared with another method.

Technically Efficient Method of Production Let us suppose that commodity X is produced by two methods by using labour and capital: Factor inputs Method A Method B Labour 3 4 Capital 4 4 In the above example, method B is inefficient compared to method A because method B uses more of labour and same amount of capital as compared to method A.

A profit maximising firm will not be interested in improvident or inefficient methods of production. If method A uses less of one factor and more of the other factor as compared with any other method C, then method A and C are not directly comparable. For example, let us suppose that a commodity is produced by two methods: The choice of any particular technique from a set of technically efficient techniques or methods is an economic one, based on prices and not a technical one. In a production function, the dependent variable is the output and the independent variables are the inputs.

For simplicity, only the inputs of labour and capital are considered independent variables in a production function. Normally, land does not enter the production function explicitly because of the implicit assumption that land does not impose any restriction on production. However, labour and capital enter production explicitly. The production function is based on an implicit assumption that the technology is given. This is because an improvement in technical knowledge will lead to larger output from the use of same quantity of inputs.

It can be used to compute the least- cost factor combination for a given output or the maximum output combination for a given cost. Knowledge of production function may be helpful in deciding on the value of employing a variable factor in the production process. As long as the marginal revenue productivity of a variable factor exceeds its price, it will be profitable to increase its use. When the marginal revenue productivity of the factor becomes equal to its price the additional employment of the factor should be stopped.

Since, the production function shows the returns to scale it will help in the decision making. The opposite will be true if the returns to scale are increasing. Fixed Proportion Production Function A fixed proportion production function is one in which the technology requires a fixed combination of inputs, say capital and labour, to produce a given level of output. There is only one way in which the factors may be combined to produce a given level of output efficiently.

In this type of production, there is no possibility of substitution between the factors of production. This is shown in Fig. The isoquant Q1 passing through the point A1 shows that one unit of output is produced by using 2 units of capital and 3 units of labour. In other words, the capital-labour ratio is 2: In this case with 2 units of capital, any increase in labour beyond 3 units will not increase output and, therefore, labour beyond 3 units is redundant.

Similarly, with 3 units of labour, any increase in capital beyond 2 units is redundant. The kink point shows the most efficient combination of factors. The capital labour ratio must be maintained for any level of output.

Thus isoquant Q2 passes through the point A2. The line OA describes a production process, that is, a way of combining inputs to obtain certain output. The slope of the line shows the capital-labour capital ratio. The fixed proportion pr production function is characterised ed by constant returns to scale, that is, a proportionate increase in inputs leads to a proportionate increase in outputs. This type of production function provides the basis for the input inpu - output analysis in economics.

Variable Proportions Production Function The variable proportion production function is the most familiar production function.

In this case, a given level of output can be produced by several alternative combinations of factors of production, say capital and labour.

It is assumed that the factors can be combined in infinite numberr of ways. The common level of output obtained from alternative combinations of capital and labour is given by an isoquant Q in Fig.

Variable Proportions Production Function The isoquant Q is the locus of efficient points of factor combinations to produce a given level of output. The isoquant is continuous, smooth and convex to the origin. It assumes continuous substitutability of capital and labour over a certain range, beyond which factors cannot substitute each other.

Since ce the variable proportions production function is the most common we discuss below in detail the isoquant representing the variable the proportions production function.

There is a need to take into consideration the time factor in the discussion on the production. Thus, in this section we consider the behaviour of production in the short-run and long-run.

The short run is a phase in which the organisation can alter manufacturing by changing variable factors such as supplies and labour but cannot change fixed factors such as capital. The long run is a phase adequately long so that all factors together with capital can be altered.

The factors which can be increased in the short run are called variable factors, since they can be easily changed in a short period of time. Hence, the level of production can be increased within the limits of existing plant capacity during the short run. Thus, the short run production function proves that in the short run the output can be increased by changing the variable factors, keeping the fixed factors constant.

In other words, in the short run the output is produced with a given scale of production, that is, with a given size of plant.

The behaviour of production in the short-run where the output can be increased by increasing one variable factor keeping other factors fixed is called law of variable proportions. The size of plant can be varied in the long run and, therefore, the scale of production can be varied in the long run. The long run analysis of the laws of production is referred to as laws of returns to scale. Explain Production Function.

What are the uses and types of Production Function? Explain short and long run production function. Discussion Discuss which is the technically efficient method of production out of the two given in the table below, and why? It is derived from the production function, which describes the efficient method of production at any given time.

The production function specifies the technical relationships between inputs and the level of output. Thus, cost will vary with the changes in the level of output, nature of production function, or factor prices.

The clause 'ceteris paribus' implies that 'all other factors which determine costs are constant'. If these factors change, they will affect the cost. The technology is itself determined by the physical quantities of the factor inputs, the quality of the factor inputs, the efficiency of the entrepreneur, both in organising the physical side of the production and in making the correct economic choice of techniques.

For instance, the introduction of a better method of organising production or the application of an educational programme to the existing labour will shift the production function upwards and hence will shift down the cost curve. Similarly, the improvement of raw material, or the improvement in the use of the same raw materials will lead to a downward shift of the cost function.

Since no output is possible without an input, an increase in factor prices, ceteris paribus, will lead to an increase in the cost. The factor prices depend on the demand and supply of factors in the economy. Of all the determinants of cost, the cost-output relationship is considered as the most important one. Thus, in economic analysis the cost function is analysed with respect to output. This is because the cost-output relationship is subject to faster and more frequent changes. The relationship between cost and output is analysed with respect to short-run and long-run.

In the short-run output can be increased or decreased by changing the variable inputs like labour, raw material, etc. Thus, the short-run costs of production are segmented into fixed and variable costs.

On the other hand, in the long-run all factors can be adjusted. Hence, in the long run all costs are variable and none are fixed. Fixed and Variable The total cost TC of the firm is a function of output q.

It will increase with the increase in output, that is, it varies directly with the output. They must be paid even if the firm produces no output. They will not change even if output changes. They remain fixed whether output is large or small. In the short period, the total amount of these fixed costs will not increase or decrease when the volume of the firms output rises or falls See Table 3.

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