The diffusion of digital information and communication technologies (ICT) in public services is generally assumed to improve their performance. However, the impact of ICT on the efficiency of public services is rarely verified. This study focuses on public historical archives (PHAs), which are a widely diffuse—yet little explored—public service. It provides an assessment of the impact of a specific ICT on PHAs’ efficiency, namely the introduction of websites. The analysis adopts a two-stage approach involving the estimation of the frontier using Data Envelopment Analysis (DEA) and Window DEA. Results show that the diffusion of ICT is efficiency improving: Italian PHAs having a website are generally more efficient than others. These empirical findings are robust to the use of alternative estimators and empirical strategies in both first and second stage assessment. Finally, we suggest some directions for further research in the field.
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Several studies have employed frontier approaches to assess the relationship between ICT investment, productivity and technical efficiency: Liao et al. (2016) used stochastic frontier model to assess the impact of ICT for the economic growth in the US whereas Lien and Peng (2001) employed DEA to examine technical efficiency of telecommunications industries in 24 OECD countries.
Table 1 excludes two archives: the National Central Archive in Rome, for its specificity, and the archive of Ferrara for lack of data.
We do not account for a potential source of heterogeneity in the sample deriving by online access which is not equally practiced across archives. However, this aspect does not endanger the reliability of our analysis since the current extent of online access is very limited, and often requires users to access from PHAs’ internet workstations (i.e. such users are also visitors).
See Guccio et al. (2016) for a more detailed description of MiBACT’s projects involving IT and the use of internet.
Since the exact date when a website becomes fully operational is not known, in Sect. 4 we also consider 2008 and 2010 as cut-offs, showing that our cut-off choice does not affect the results.
Simar and Wilson (2007) presents a survey of developments devoted to include noise in non-parametric frontier estimators and proposes a stochastic version of DEA and FDH estimators.
The rationale behind bootstrapping is to simulate a true sampling distribution by simulating their Data Generating Process—DGP—here the outputs from DEA (Simar and Wilson 2008). More in particular, the process relies on constructing a pseudo-data set and re-estimating the DEA model with this new data set. Repeating the process many times allows for achieving a good approximation of the true distribution of the sampling.
See Simar and Wilson (2008) for the technical detail of the bootstrap procedures.
The Banker (1996) test shows that in our sample we can reject the null hypothesis of CRS at 5 percent level of significance. Results are available upon request.
An alternative way to study the efficiency change and the catch up effect is to compute and analyse the Malmquist index. However, Asmild et al. (2004) show that the use of Malmquist index on scores estimated through WDEA is inappropriate and leads to incorrect results.
In spite of the advantages of WDEA it must be mentioned that, although this method allows to exploit panel data to assess efficiency over time, it is not a dynamic model such as those developed by Färe and Grosskopf (1996), Nemoto and Goto (1999, 2003), Tone and Tsutsui (2010), i.e. it does not model DMUs dynamic behaviour and does not take into account that some inputs are quasi-fixed and carried over along subsequent periods. While dynamic alternatives allow to model choices in a more realistic way in general, their advantage is limited in our context. In fact, dynamic models are designed to deal with strategic long term choices of investment that imply the diversion of resources usually employed to produce the outputs. Thus, investment reduces the output in the short run, resulting in an overestimation of inefficiency through traditional DEA. In our setting WDEA is thus preferable to get a more conservative estimation of the potentially positive impact of websites on PHAs efficiency.
As common in DEA framework we pooled the data for consistency of the efficiency estimates (Simar and Wilson 2008).
The separability condition requires that contextual factors do not affect production possibilities, i.e. the shape and the level of the frontier (Simar and Wilson 2007, Daraio et al. 2018). However, the variables that we employ regard mainly the presence and use of websites, which are related to the demand for such services and thus may reasonably affect the distribution of efficiency scores inside the production possibility set but presumably not the attainable set and its frontier. Furthermore, in what follows, we also perform the Banker and Natarajan (2008) estimator does not require such condition, which makes us quite confident on the robustness of our findings (Banker et al. 2019).
As observed by Wooldridge (2002), feasible generalized least squares estimator is prudently employed when dealing with simple forms of autocorrelation or group wise heteroskedasticity.
A detailed discussion on this estimate and its reliability can be found in Guccio et al. (2018a).
YEAR_SINCE defines a subsample since some PHAs did not have a website even in the sample, as reported in Fig. 2. W_VISIT defines a subsample because observations required additional cleaning procedures and are also characterized by several missing data.
We thank the General Direction for Italian Archives for its support in the collection of data.
Such outcomes are obtained through the Simar and Wilson (2000) bootstrap procedure with 2000 bootstrap draws, estimated by using the software package FEAR 1.15 (Wilson 2008), to check for the robustness of the DEA findings with respect to the sampling variation. However, Simar and Wilson (2008) point out that the bias correction obtained with bootstrap procedures introduces additional “noise” in the efficiency estimates and show that the bias correction provides valid inference only if the ratio of the estimated bias to the variance satisfies some conditions. As a caution rule, they suggest that the bias correction should not be used if correction is larger than four times the variance of efficiency scores obtained from all bootstrapped pseudo-samples, as in our estimation. Thus, we do not focus on such estimates in the remainder of the paper.
We consider three geographical areas: North (Emilia Romagna, Friuli, Liguria, Lombardia, Piemonte, Trentino, Veneto), Centre (Lazio, Marche, Toscana, Umbria), South (Abruzzo, Basilicata, Calabria, Campania, Molise, Puglia, Sardegna, Sicilia).
Results based on T2012 are shown in the “Appendix”.
We have 4 windows over the period 2009–2014 because, when a new period is introduced into the window, the earliest year is dropped. Thus, the first window includes the first 3 years of the period: 2009, 2010 and 2011. In the second window, the year 2009 is excluded and the year 2012 is included and so on. Since WDEA treats a DMU independently across the entire period, 4 three-year windows considerably increase the number of observations of the sample. To provide robustness to our results we also run the estimate setting k = 4. Related estimates, which confirm our main results are available upon request.
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We are thankful to the Italian Directorate General of Archives (DGA) and the Public Historical Archive of Catania for the support in the collection of the data. We also wish to thank two anonymous referees for their careful review and the Editor Professor Samuel Cameron for his advice. The usual disclaimer applies.
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Guccio, C., Martorana, M., Mazza, I. et al. Back to the Future: Does the use of information and communication technology enhance the performance of public historical archives?. J Cult Econ 45, 13–43 (2021). https://doi.org/10.1007/s10824-020-09385-1
- Public services
- Cultural heritage
- Non-parametric frontier