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In economics, a measure of the sensitivity or responsiveness of a variable corresponding to a change in another variable. Common applications in empirical research include price or income elasticity of demand. For example, what is the percent change in quantity demanded for gasoline when price is increased by 1%?

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I have some panel data for various products (UPCs) below purchased at various price points across various stores across time (the data is by shopper-date-store-product). I'm trying to sort out the ...
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I have retail price and sale data for the same 300 products (around 100 each in three categories ) in 10 stores spread in three states observed weekly for 5 years. How can I estimate cross price ...
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I am trying to better understand Poisson models whose coefficients are expressed in log-counts because counts are skewed. See example estimates on synthetic data below. Some suggest interpreting log-...
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If I have a regression in with logs taken of both sides to give the equation: $ln(y) = \beta_0 + \beta_1 ln(x)$ and need to calculate the expected change in $y$ for a given $x$. I can see from reading ...
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Many of you will be familiar with the use of the log log linear regression model to estimate elasticity. I am in this situation where I can get zero demand, the dependent variable, which obviously ...
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When we try to estimate elasticities by regression, we usually estimate the following regression model: $$ln(y) = \beta_0 + \beta_1 ln(x_1) + \dots + \epsilon$$ When we expect to have endogenous ...
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It is common econometric disciplines to model an baseline + incremental quantity due to treatment. E.g baseline sales + incremental sales(due to marketing). It is common to deploy loglog models to ...
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How does one estimate price-elasticity and cross-price elasticity using cross-sectional household survey data? Note that household survey data usually do not include price information. The literature ...
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I estimated a hurdle negative binomial regression model with zero-truncated negative binomial model as the count component in R using the pscl package. I wish to present elasticities for the count ...
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Here're the results of a multi-variable regression analysis run by Stata to test the effects of the three factors on the price elasticity of supply, which is the dependent variable. The coefficients ...
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I want to find input demand elasticities using a cost function. Input quantities and input prices are available for individual farmers for 5 food crops and 5 years (2015-2019). But farmers may vary ...
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I am working with pseudo-panel data (UK Cost of Living and Food Survey), which means I am observing expenditure data for different households every month over ~10 years with data on demographic ...
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I am estimating a time series 2SLS, ECM model, for electricity consumption. The system has a demand equation: The price is endogenous in the demand equation, and therefore, I also estimate a price ...
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I have weekly data per single SKU and for more than 500 point of sales. Data embeds base price, quanity sold, holidays, temperature, market activities (cut-price, display, leaflets) and so on. I want ...
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I am estimating a 2SLS using a time series simultaneous equation ECM. The purpose is to estimate the price elasticity of electricity demand. Assume that both price and demand are I(1) variables, ...
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Which is the correct way to compute the elasticity in this log log regression? Context: When having an log log regresion: log(Y) = log(B0) + B1 log(X), being Y= Demand and X Price, B0 intercept and B1 ...
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I am executing a lightGBM model to forecast my units sold (qty) over a period of time. Objective is to run a model for each product group and be able to capture the trends, price elasticity, etc and ...
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I am building a price elasticity model using linear regression: log(demand) ~ 1 + log(price) + ... Does it make sense to use L1 and/or L2 regularization to prevent ...
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Consider the following two regression models using data from the table below. $ln(wage)=\beta_0+\beta_1 female+u$ $ln(wage)=\gamma _0+\gamma_1 male+v$ wage female male 10 1 0 20 1 0 30 1 0 40 1 0 50 ...
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I have a dataset like this: Fileds Profit x Product: It is the variable that I can change, and is the independent variable. ...
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I was wondering what the best method to go about this would be. I have one year's worth of data and its related to air-travel. So I have ticket fares, passengers sent, discount applied on each ticket ...
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I have price volume data for 3 states for which I want to calculate price elasticity for each state. The model has the following setup: $$ \ln(Y)=A_1+ A_2\ln(P) +A_3D_1 +A_4D_2+ A_5\ln(P)D_1 +A_6\ln(P)...
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I am attempting to model the decreasing price elasticity/response for a good. I need to control for place and time features and available alternatives. Besides this, I also need to add time and ...
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We know from the following sources, "Halvorsen, R. and Palmquist, P., The Interpretation of Dummy Variables in Semilogarithmic Equations, American Economic Review, Vol. 70, 1980, pp. 474-475.&...
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Question The question is: how to smooth out kinks in individual demand curves in a GBDT model without underfitting on the price variable? Background We have some GBDTs demand models already in place (...
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I am working on a project to try understand Linear Regression a bit deeper (they say experimenting is key and getting lost is part of the process) :( In this project, let's assume I have a watch shop. ...
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I performed a log-log regression and have a negative regression coefficient. I'm interpreting my results to indicate that a 1% increase in X is associated with a .28% decrease in Y. However, for ...
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I need to be corrected if i have something wrong : the elasticity of the demand is calculated : dq/dp if q is the quantity and p the price so to calculate it i take two prices p1 and p2, if i have ...
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Ive got a regression in the form log(y) = a +b1x1 + b2x1^2 + b3x2 + b4x3 + b5* log(x4). I've interpreted my coefficients as they should be interpreted.I figured out the quadratic and e^b3 and e^b4 are ...
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I'm running an analysis of two products, X and Y, and I'm particularly interested in understanding the elasticities. However, I'm struggling to interpret the results. I'm using a log-log model, and in ...
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I am trying to build a random forest-based market mix model, wherein I want to calculate the contribution of each of my X variables towards the target. Typical MMM problem statement, but here am not ...
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How to find the elasticity of a negative binomial regression when the independent variables are numeric, categorical, or dummy variables? Edit: For example, ...
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I am working on an price optimization problem for a Real Estate company. Basically, we'd like to optimize their rental price to maximize revenue on their properties. I have submarket level data such ...
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The comment in the solution says : We display all elasticities of purchase probability on the same plot. We observe that the Career-focused segment are the least elastic when compared to the rest. So, ...
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I'm trying to model price elasticity based on price changes and I'm wondering what is the best way to do it. My data is at the individual customer level and there's a 0/1 indicator for whether they ...
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Lnyt=3.493+0.231xt-0.13Dtxt+1.024D2-0.541D3+t The data is quarterly and D2 and D3 are significant seasonal dummy variables I included. Additionally, Dtxt is the slope interaction dummy ...
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Specifically, suppose we are estimating $$ \ln(y)=\beta_1\ln(x) + \epsilon $$ I understand that $\beta_1 = \frac{\partial \ln(y)}{\partial \ln(x)}$ which is the elasticity of $y$ with respect to $x$ ...
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Let us assume that $Y_t$ can be described with an ARMAX process, including an exogenous covariate $X_t$, of the following form: \begin{equation} log(Y_t)=\phi_1log(Y_{t-1})+\phi_{12}log(Y_{t-12})+\...
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So let's say I have a multiple regression as such: Y = constant + a1X1 + a2X2 + a3X3 Here ac is the coeffcient corresponding to the Xc Y is a normal variable constant is a non-zero constant X1 is ...
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Consider a standard "log-log" linear regression model like this: $\log(y_i) = \log(a_i + b_i)\delta + \epsilon_i$, where $y$ is the dependent variable, $a$ and $b$ are two independent variables, and ...
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I have just started working on price elasticity and I have some fundamental question. Question 1: I have daily price and sales data for a product, now if I want to calculate the price elasticity ...
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I am currently doing local sensitivity analysis on a model that has 40 input parameters. I varied the base case value by 10% within the range of [-1, 1]. While doing so the average change (here, I ...
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So let's say I have 100 data points which contains the price and sales of a product. Just to start I assume that the relationship is of the form Q = a - b*P where P ...
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According to this article, calculating elasticity of demand for different models is: I generate data for 5% reduction in prices with a corresponding 10% increasing in sales: price elasticity = (+10%/-...
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I have approximately 2000 daily data which contains total daily sales and median price of sales for a particular product. I read the paper but the level of bayseian math is too high for me but from ...
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I have the following model, and I am not sure how to interpret the elasticity of the interaction term (log-log coefficients): Log(member) = 3.61 + 0.52 Log(Poor) - 0.26 Log(Sick) + 0.04 (Log(poor) * ...
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For a data if I calculate Elasticity using 1) log-log model with Elasticity = Beta and 2) Calculate elasticity in Level-Level Model with elasticity = beta *(X/Y) should the resultant value of ...
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I have a case where I do not have many regular prices, but I have many discounts (different kind) which last a different number of days. Is there something like discount elasticity and how to adjust ...
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I have few product categories eg prod1 prod2. Each category have similar products. So prod1 has 3 similar products with slight difference in features and prod2 has 5 products with slight differences. ...
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I would like to estimate elasticity of exchange rate on export. The specification takes the following form: $$Exp=\alpha+\beta_0REER+\beta_1GDP^{p}+\epsilon$$ where, $Exp$ is export growth calculated ...
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