Price Markup Research Articles

A note on labor share, price markup and monetary policy

This paper extends Kaplan and Zoch’s (2020) insight that the total labor share is neither solely nor inversely determined by the price markup in a medium scale dynamic stochastic general equilibrium (DSGE) model with nondurables and durables. Our calibration results show that when monetary policy shocks and markup shocks are set to be positively (negatively) correlated, monetary contraction increases (decreases) total labor share and price markup. The total labor share is countercyclical (procyclical) conditional on a monetary policy shock.

Effects of a mandatory local currency pricing law on the exchange rate pass-through

This paper discusses whether Law 28300 of 2004, that required Peruvian firms to express their prices in Peru’s currency in a context of high price dollarization, affected the exchange rate pass-through (ERPT). We hypothesize that the enactment of the Law introduced menu costs for firms that used to set their prices in dollars, prompting several of them to make a permanent switch to pricing in local currency. Using disaggregated consumer price index (CPI) data, we find that, following passage of the Law, the ERPT was completely offset for non-durable goods with dollarized prices, and partially offset for durable goods with dollarized prices. These effects may vary due to differences in imported component shares, market power, and markup pricing.

The impact of end-user market integration and the smart grid on electricity retailers in the Nordic region

The Nordic end-user market for electricity has recently been the subject of significant changes. The energy authorities within the Nordic countries have been working intensively to create a fully operational common electricity retail market, and all customers were due to have smart meters installed by the end of 2019. These changes are of particular concern for the suppliers of retail electric power, as competition will increase and the retail products and offers related to the smart grid and specific customers’ needs will gain importance. With the help of a mixed complementarity problem formulation that describes a simplified market setting with two competing retailers, we analyze the impact of the pending market changes on electricity retailers’ price markup and profit.

Estimated DSGE Model for Macroeconomic Analysis in a Small-Open Economy: A Ghanaian Perspective

The study develops a standard representative-agents’ New Keynesian model for macroeconomic analysis in a developing African economy. Using Bayesian estimation techniques and Ghanaian dataset, the core objective of the paper is to determine the best suited monetary policy rule for Ghana. After determining the most appropriate monetary policy rule for Ghana, the model is then used to ascertain the dominant macroeconomic shocks to inflation, output and interest rate. The basic finding is that a forward-looking Taylor rule - where authority reacts to one-period-ahead inflation deviation from target alongside current output gap - is the most appropriate monetary policy rule for Ghana. In addition, variations in output are mainly driven by price markup, labour supply, monetary policy and productivity shocks across the forecast horizons. This suggests that monetary policy still matters for output growth in Ghana in the short-to-long run. The dominant determinants of inflation are exchange rate risk premium and price mark-up shocks. The dominant drivers of domestic interest rate are price mark-up, domestic monetary policy and government spending shocks are across forest horizon. By implication, upholding exchange rate stability alongside fiscal prudence is very critical for achieving the broad macroeconomic objectivities in Ghana.

Observed expectations, news shocks, and the business cycle

This paper exploits information from the term structure of survey expectations to identify news shocks in a DSGE model with rational expectations.We estimate a structural business-cycle model with price and wage stickiness. We allow for both unanticipated and anticipated components (“news”) in each structural disturbance: neutral and investment-specific technology shocks, government spending shocks, risk premium, price and wage markup shocks, and monetary policy shocks.We show that the estimation of a standard DSGE model with realized data obfuscates the identification of news shocks and yields weakly or non-identified parameters pertaining to such shocks. The identification of news shocks greatly improves when we re-estimate the model using data on observed expectations regarding future output, consumption, investment, government spending, inflation, and interest rates - at horizons ranging from one-period to five-periods ahead.The news series thus obtained largely differ from their counterparts that are estimated using only data on realized variables. Moreover, the results suggest that the identified news shocks explain a sizable portion of aggregate fluctuations. News about investment-specific technology and risk premium shocks play the largest role, followed by news about labor supply (wage markup) and monetary policy.

ON PHASE SHIFTS IN A NEW KEYNESIAN MODEL ECONOMY

The purpose of this paper is to focus directly on the phase shift. For one thing, we ask whether a New Keynesian sticky-price model economy can account for both countercyclical prices and procyclical inflation. We present findings in which the price level is countercyclical and the inflation rate is procyclical. We proceed to use the model economy as an identification mechanism. What set of individual shocks are necessary to account for the phase shift? That set contains the price markup shock. Next, we ask what set of shocks are sufficient to account for the phase shift. This set contains three elements: the price markup and wage markup shocks along with the government spending shock. The results are important as a building block. We infer that price stickiness is an important model feature; without price stickiness, we are in the real business cycle economies that Cooley and Hansen studied. But, it raises further questions. For instance, is price stickiness of the Calvo form—the one used here—necessary to explain the phase shift?

Impact of environmental labeling certification on firm performance: Empirical evidence from China

Environmental labels are designed to signal environmental and health information on products throughout their life cycle to consumers and other stakeholders. Investigating A-share listed manufacturing firms in China for the 2004–2018 period, this paper sheds new light on the nexus of environmental labeling certifications and firm performance. We find that there is a grouping difference in firm performance between treatment firms and comparison firms, no matter whether measured by ROA, Tobin’s Q, or TFP. Based on the difference-in-difference (DID) regression, we show that manufacturing firms significantly increase their financial performance and productivity after obtaining environmental labeling certifications. Our research also reveals that the effects of environmental labels on firm performance stem from both the labeling effect and technical factor. The results are robust when we use the micro-level DID model. Further examination shows that the intervention effect is mainly driven by the mechanism of price markup rather than by market share.

Towards the Derivation of the Cambridge Equation with Expanded Reproduction and Markup Pricing

Does the Cambridge equation, in which the rate of profits in a steady state is equal to the quotient of the rate of growth and the savings rate out of profits, hold in an economy with widespread non-competitive markets? This article presents a multiple-good model of markup pricing in an attempt to answer this question. A balance equation is derived. Given competitive conditions, this model can be used to derive the Cambridge equation. The Cambridge equation also holds in a special case of markup pricing, with one capital good and many consumption goods being produced. No definite conclusions are reached in the general case.

Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry

We quantify the importance of imperfect competition in the US construction industry by estimating the size of rents earned by American firms and workers. To obtain a comprehensive measure of the total rents and to understand its sources, we take into account that rents may arise due to markdown of wages in the labor market, or markup of prices in the product market, or both. Our analyses combine the universe of US business and worker tax records with newly collected records from US procurement auctions. We use this data to identify and estimate a model where construction firms compete with one another for projects in the product market and for workers in the labor market. The firms may participate both in the private market and in government projects procured through auctions. We find evidence of considerable wage- and price-setting power. This imperfect competition creates sizable rents, three-fourths of which is captured by the firms. The incentives of firms to mark down wages and reduce employment due to wage-setting power are attenuated by their price-setting power in the product market.

Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry

The primary goal of our paper is to quantify the importance of imperfect competition in the U.S. construction industry by estimating the size of rents earned by American firms and workers. To obtain a comprehensive measure of the total rents and to understand its sources, we take into account that rents may arise both due to markdown of wages and markup of prices. Our analyses combine the universe of U.S. business and worker tax records with newly collected records from U.S. procurement auctions. We first examine how firms respond to a plausibly exogenous shift in product demand through a difference-in-differences design that compares first-time procurement auction winners to the firms that lose, both before and after the auction. Motivated and guided by these estimates, we next develop, identify, and estimate a model where construction firms compete with one another for projects in the product market and for workers in the labor market. The firms may participate both in the private market and in government projects, the latter of which are procured through first-price sealed-bid auctions. We find that American construction firms have significant wage- and price-setting power. This imperfect competition generates a considerable amount of rents, two-thirds of which is captured by the firms. Lastly, we use the estimated model to perform counterfactual analyses which reveal how increases in the market power of firms, in the product market or the labor market, would affect the outcomes and behavior of workers and firms in the construction industry. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Nonparametric Identification of Production Function, Total Factor Productivity, and Markup from Revenue Data

Commonly used methods of production function and markup estimation assume that a firm's output quantity can be observed as data, but typical datasets contain only revenue, not output quantity. We examine the nonparametric identification of production function and markup from revenue data when a firm faces a general nonparametri demand function under imperfect competition. Under standard assumptions, we provide the constructive nonparametric identification of various firm-level objects: gross production function, total factor productivity, price markups over marginal costs, output prices, output quantities, a demand system, and a representative consumer's utility function.

Nonparametric Identification of Production Function, Total Factor Productivity, and Markup from Revenue Data

Commonly used methods of production function and markup estimation assume that a firm's output quantity can be observed as data, but typical datasets contain only revenue, not output quantity. We examine the nonparametric identification of production function and markup from revenue data when a firm faces a general nonparametri demand function under imperfect competition. Under standard assumptions, we provide the constructive nonparametric identification of various firm-level objects: gross production function, total factor productivity, price markups over marginal costs, output prices, output quantities, a demand system, and a representative consumer's utility function.

A Scalar-Parameterized Mechanism For Two-Sided Markets

We consider a market in which both suppliers and consumers compete for a product via scalar-parameterized supply offers and demand bids. Scalar-parameterized offers/bids are appealing due to their modeling simplicity and desirable mathematical properties with the most prominent being bounded efficiency loss and price markup under strategic interactions. Our model incorporates production capacity constraints and minimum inelastic demand requirements. Under perfect competition, the market mechanism yields allocations that maximize social welfare. When market participants are price-anticipating, we show that there exists a unique Nash equilibrium, and provide an efficient way to compute the resulting market allocation. Moreover, we explicitly characterize the bounds on the welfare loss and prices observed at the Nash equilibrium.

Using Deep Learning to Overcome Privacy and Scalability Issues in Customer Data Transfer

Customer privacy is increasingly important to marketers. High-profile breaches of databases containing sensitive customer information, and the growing need to build the infrastructure required to support analysis of big data, present nontrivial obstacles to researchers seeking individual-level customer data from firms. In this paper, we show that recent developments in machine learning may enable firms to transfer a generative model, instead of data, thus potentially obviating the process of anonymizing and sampling customer data for release, for use in a variety of analytic use cases. We demonstrate the efficacy of a specific deep learning model, Generative Adversarial Networks (GANs), in preserving desired characteristics of original data. In real-world settings, we find that GANs can double the accuracy as compared to the best benchmark methods. We also demonstrate that GANs can be used to solve marketing problems of price markups for optimal profits and customer targeting, and that a single GAN can tackle multiple marketing problems. Furthermore, GANs have volume and velocity advantages, as the size of informational transfer grows according to model complexity, and it can readily handle real-time data streams.

Inventory and pricing decisions for an imperfect production system with quality inspection, rework, and carbon-emissions

The present paper considers the effect of imperfect quality items on a production system which further undergoes inspection and rework. The demand of the product is price reliant. Two situations to handle the imperfect items are analyzed: selling them at a reduced price and reworking them. The demand is assumed to meet with perfect products in either case. Further, the study incorporates the carbon-emissions borne during production of goods and their holding in the inventory system. The model aims at maximizing the profit function by jointly optimizing mark-up price and production quantity. To demonstrate model characteristics, numerical and sensitivity analysis are also presented.

The Labor Theory of Value and Sraffa's Standard Commodity With Markup Pricing

This article demonstrates relationships that are transparent in Sraffa’s standard system hold even when relative rates of profit vary persistently among industries. Even with such variations, total constant capital, total variable capital, total surplus value, and the rate of profits are unaltered by evaluation at labor values and at prices of production in Sraffa’s standard system. These results buttress those who see in the standard commodity a solution for Marx’s so-called transformation problem.

Selection of Promotion Channels for Organic Products in the Internet Environment

In Russia the development of the organic product market faces the following limiting factors: high price, insufficient awareness and low physical availability of bioproducts for the population. The use of modern Internet technologies can have a positive impact on solving these problems. Direct selling through online-stores or corporate websites allows to control adequate price markup on products. The variety of social Internet communications can be successfully used in increasing public awareness about organic products and the peculiarities of choosing them. Moreover, bearing in mind the specific character of bioproducts which have a low shelf life, online sales are necessary to ensure filled customer demand. Thus, the issues of choosing the most optimal channels for promoting organic products in the Internet are important and well-timed. The purpose of the article is to identify the most effective channels in promoting organic products in the Russian market.The implementation of the set tasks was achieved by means of using general scientific methods: analysis, synthesis. The statistical methods were also used during processing and synthesis of statistical data and their generalization in the most informative form i.e. tables, figures. The article identifies the most efficient channels for promoting organic products in the Internet environment from the point of view of an enterprise’s goals. The author defines the KPI assessments of its effectiveness for each online channel. On the one hand, understanding the peculiarities of using various Internet channels to promote organic products can have a positive impact on the consumer demand in general. On the other hand, it will allow making the most efficient use of Internet technologies in the general strategy of promoting an enterprise.

The Past and Future of Keynesian Economics: A Correction

This note clarifies an issue raised in an earlier article in this Review by the same author, concerning the coherence and plausibility of mark-up pricing in relation to competition.

Bullwhip effect in pricing under different supply chain game structures

Bullwhip effect in pricing (BP) refers to the amplified variability of prices in a supply chain. This paper analyzes the occurrence of BP under three game scenarios (e.g. a simultaneous, a wholesale-leading, and a retail-leading) for three types of demand functions (e.g. a log-concave, an isoelastic, and a negative exponential). Cost pass-throughs and BP ratios are calculated analytically for an N-stage supply chain, and then the price fluctuations in various supply chain game structures are illustrated through simulations. The results indicate that in the case of optimal markup pricing games, the occurrence of BP depends on the demand functions. This study also shows that, BP occurs in varying magnitudes for different types of games. Finally, a relation between price variations and corresponding markup profits are also discussed.

Are Price-Cost Markups Rising in the United States? A Discussion of the Evidence

A number of recent papers have argued that US firms exert increasing market power, as measured by their markups of price over marginal cost. I review three of the main approaches to estimating economy-wide markups and show that all are based on the hypothesis of firm cost minimization. Yet different assumptions and methods of implementation lead to quite different conclusions regarding the levels and trends of markups. I survey the literature critically and argue that some of the startling findings of steeply rising markups are difficult to reconcile with other evidence and with aggregate data. Existing methods cannot determine whether markups have been stable or whether they have risen modestly over the past several decades. Even relatively small increases in markups are consistent with significant changes in aggregate outcomes, such as the observed decline in labor’s share of national income.