The UK-JEDI Methodology

The overall approach, followed by top-down models such as JEDI, is to combine the use of model plant data to estimate direct employment generation and (IO) data multipliers to estimate indirect and induced employment. While this is a well-established method of calculating the employment supported by a given project, it is not without limitations. Results should therefore be interpreted in the context of these constraints. 

Most importantly, the methodology assumes that relative prices remain unchanged, and therefore that impacts making changes elsewhere in the energy sector, such as increased investment and electricity costs, cannot be determined. 

UK-JEDI does not estimate constraints in resources, which can also be associated with price increases. The model assumes that all inputs, including necessary labor and investment, are available and at the same cost regardless of the quantity needed.

The IO tables are also a limiting factor, as they represent an estimate of the structure of an economy in a given year and are subject to change. Technology, relative price changes, and several other factors drive these changes. For example, the price of one input may drive a company to substitute a different input or change the location from which they purchase the input. This represents a limitation because data are often lagged for some time.

Moreover, IO tables are typically not updated every year, which may introduce errors and uncertainties resulting from overestimating the amount of employment likely to be generated by an increased demand. The most recent data available from the ONS website reports IO coefficients from 2019, which are very likely to change over the 2020–2030 timeframe. Although such simplification would most likely affect the employment figures, the difference may be small: a study on US agriculture sector employment pointed out that multipliers from IO tables constructed 10 years apart differ by only 2%.