industry

Simulated data on industrial development from 1983 to 2014 in 10 imaginary regions.

Inference functionalities for distributed-lag linear structural equation models (DLSEMs). DLSEMs were recently proposed by Magrini et al. (2016) <ISBN:978-88-619-7061-8> as an extension of linear structural causal models (Pearl, 2000) <ISBN:978-0-521-89560-6>, where each factor of the joint probability distribution is a distributed-lag linear regression with constrained lag shapes. Endpoint-constrained quadratic, quadratic decreasing and gamma lag shapes are available.

Alessandro Magrini

dlsem

Distributed-Lag Linear Structural Equation Models

industry function

A data frame with a total of 320 observations on the following 7 variables:<dl class="dl-horizontal">
 <dt><code>Region</code></dt><dd>ID of the region.</dd>
 <dt><code>Year</code></dt><dd>Year.</dd>
 <dt><code>Population</code></dt><dd>Population (number of inhabitants).</dd>
 <dt><code>GDP</code></dt><dd>Gross domestic product (1000 international dollars).</dd>
 <dt><code>Job</code></dt><dd>Employment in industry (Index, 1980=100).</dd>
 <dt><code>Consum</code></dt><dd>Private consumption (Index, 1980=100).</dd>
 <dt><code>Pollution</code></dt><dd>Greenhouse gas emissions (tonnes of CO2 equivalent).</dd>
 </dl>

Format

Industrial development — industry

A data frame with a total of 320 observations on the following 7 variables:<dl class='dl-horizontal'>
 <dt><code>Region</code></dt><dd>ID of the region.</dd>
 <dt><code>Year</code></dt><dd>Year.</dd>
 <dt><code>Population</code></dt><dd>Population (number of inhabitants).</dd>
 <dt><code>GDP</code></dt><dd>Gross domestic product (1000 international dollars).</dd>
 <dt><code>Job</code></dt><dd>Employment in industry (Index, 1980=100).</dd>
 <dt><code>Consum</code></dt><dd>Private consumption (Index, 1980=100).</dd>
 <dt><code>Pollution</code></dt><dd>Greenhouse gas emissions (tonnes of CO2 equivalent).</dd>
 </dl>

industry: Industrial development

Description

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Format