Forecasting innovative start-ups through automatic variable selection and MIDAS regressions

ABSTRACT

The paper focuses on the role that both macroeconomic indicators and financial factors play as drivers for the birth and the evolution of the Italian innovative start-ups over time. The analysis makes use of a novel machine learning algorithm, working in high-dimensional graphical models, to select, among the multitude of potential determinants, the relevant explanatory variables for the number of innovative start-ups. Being the variables involved in the analysis sampled at different frequencies, mixed data sampling models are employed for estimation and forecasting purposes. The need to reduce the number of regressors of these models, for reasons related to their estimability, is met by resorting to principal component analysis of the potential determinants. An empirical application to the set of Italian innovative start-ups, either in their entirety or split according to some specific requirements, highlights the effectiveness of this approach. The analysis results provides useful information for the assessment of national innovation policies and for the evaluation of the capability of the innovative start-ups to persist and contribute at the recovery during the actual crisis still affected by the pandemic.

KEYWORDS:

• Innovative start-ups
• MIDAS
• U-MIDAS
• variable selection
• COVID-19

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 See website: http://start-up.registroimprese.it/start-up/index.html.

2 In the construction of these subgroups we have excluded the IS that meet both the 1st and 2nd requirements (318), both the 1st and 3rd requirements (199), and also all requirements (153). Moreover, 27 IS have not been considered because there is no available information on the requirement they met A robustness check has shown that results are coherent and consistent also including IS satisfying multiple requirements.

3 These are for instance: tax incentives for investment in the capital of innovative start-ups; free and simplified access to the Guarantee Fund for SMEs; subsidized loans for innovative start-ups located throughout the country; seamless transformation into innovative SMEs; exemption from chamber rights and stamp duties; raising capital through equity crowdfunding campaigns; business internationalization services; exceptions to ordinary corporate regulations; the discipline of flexible work; extension of the deadline for covering losses; derogation from the regulations on shell companies and systematic loss companies; remuneration through equity participation instruments; exemption from the obligation to affix the compliance visa for the compensation of VAT credits; and simplified procedures in case of business failure (the so-called ‘Fail Fast’ procedure).

4 Source: www.istat.it.

5 Source: finance.yahoo.com.

6 Source: www.registroimprese.it.

7 Values of the variables sampled at lower frequencies have been repeated in correspondence to the intermediate values of the higher-sampled ones for the BPA step.

8 March 2021 is the month when started the first lockdown in Italy while the end of 2022 signs the end of almost all the COVID-19 restrictions.

9 Compared to the general case, here the variables related to the requirements met by IS have been excluded.

10 The model forecasts 969 IS for G1 in the test set, the same value of new IS in G1 actually registered in the first half of 2022 (Figure D16).

11 Also in this case the best U-MIDAS model (which outperforms the MIDAS with Almon specification) forecasts exactly the number of IS in G2, 352, within the test set (Figure D17).