International Journal of Multidisciplinary Research and Growth Evaluation  |  ISSN (Online): 2582-7138  |  Double-Blind Peer Review  |  Open Access  |  CC BY 4.0

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     2026:7/3

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN (Online): 2582-7138 | Open Access

The influence of the development level of digital economy on the competitiveness of China's manufacturing industry in foreign trade

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Volume: 6 | Issue: 3 | Pages: 65-72

Subject: Business

Country: China

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Abstract

The article selects data on digital economic development and manufacturing foreign trade from 30 provinces in China between 2012 and 2021, using a two-way fixed effects model to empirically investigate the impact of digital economic development levels on the competitiveness of manufacturing foreign trade and the moderating effect of manufacturing export structure. The study finds that an increase in the level of digital economic development can significantly enhance the competitiveness of manufacturing foreign trade. The export structure of manufacturing plays a positive moderating role. Heterogeneity analysis based on geographical location reveals that the promotion effect of digital economic development levels on the competitiveness of manufacturing foreign trade is more pronounced in central and eastern regions.

How to Cite This Article

Yuting Dai, Renxiang Lu (2025). The influence of the development level of digital economy on the competitiveness of China's manufacturing industry in foreign trade . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 6(3), 65-72.

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  1. 0. 398 Internet Broadband Subscribers(10,000households\0.079 Mobile Phone Penetration Rate(unitsper100people\0.089 Numberof Domain Names(10,000\0.060 Numberof IPv4 Addresses(10,000\0.084 Lengthof Long-Distance Optical Cable Lines(10,000km\0.086 Digital Industrialization0.236 Telecom Business Revenue(100millionyuan\0.063 Software Industry Revenue(10,000yuan\0.046 Software Revenueas%of Regional GDP(%\0.060 Employmentin Information Services(10,000people\0.066 Industrial Digitization0.184E-Commerce Sales(100millionyuan\0.060 Express Delivery Volume(10,000parcels\0.035 Digital Inclusive Finance Index0.090 Digital Technology Innovation0.182 Technology Contract Transaction Value(100millionyuan\0.045 Numberof Patent Grants(10,000\0.057 Regional R&DExpenditure Intensity0.080 International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com69|Page4.2.3 Regulatingvariables: manufacturingexportstructure Thispaperselectstheexportstructureofmanufacturingasanintermediaryvariable, drawingon Yin Zhongming'smeasurementmethod, andusesthetechnicalcomplexityofhigh-techproductexportstorepresentit. Thehigherthisvalue, themoreitindicatesthathigh-techproductsaccountforalargerproportionin China'smanufacturingexports, withhigheraddedvalue, reflectinganimprovementinforeigntradecompetitiveness. Thespecificcalculationmethodfollows Hausmann(2007\, whichcanbeexpressedas:(4\(5\Amongthem, krepresentsthehigh-techindustryproductkinacertainperiod, Yjisthepercapita GDPofprovincej, Productkreferstothetechnicalcomplexityofexportinghigh-techindustryproductkinacertainperiod, jrepresentstheprovince, Expyjisthetechnicalcomplexityofexportinghigh-techproducts, Xjrepresentsthetotalexportvalueofhigh-techproductsfromprovincej, xjkrepresentstheexportamountofhigh-techindustryproductkfromprovincej.4.2.4 Controlvariables Thecontrolvariablesselectedinthispaperinclude: thedegreeofopenness(open\, representedbytheratiooftotalimportsandexportsto GDP; industrialdevelopmentlevel(indus\, indicatedbytheratioofsecondaryindustryvalueaddedtoregional GDP; foreigndirectinvestmentlevel(fdi\: thispaperusesactualforeigndirectinvestmentasthedataforthisindicator; R&Dintensity(res\measuredbytheproportionofinternal R&Dexpenditureintheprovince's GDP; governmentsupportlevel(gov\,4.3 Sampleselectionanddatasources Duetothelackofdataforsomeyearsin Tibet, Hong Kong, Macao, and Taiwan, thisstudyfocusesontheremaining30provincesof Chinafrom2012to2021, generatingatotalof300balancedpanelobservations. Theoriginaldatausedinthisstudycomesfromthe"China Statistical Yearbook,""China Scienceand Technology Statistical Yearbook,""China Labor Statistical Yearbook,""China Industrial Statistical Yearbook,""China Financial Yearbook,"andthe National Research Networkdatabase. Formissingvaluesinindividualyearsandprovinces, linearinterpolationisusedtofillthem. Belowarethedescriptivestatisticsforeachvariable: Table2: Descriptivestatisticsofvariables Variable Sample Size Mean Std. Dev. Min Max TC3000.2390.333-0.6010.786 Dig3000.1940.1140.0520.630 Expy3008.9960.6167.51410.51 Open3000.2640.2680.0151.217 Indus3000.3290.0760.1150.469 Fdi30012.791.7317.41214.88 Res3000.0210.0050.0100.038 Gov3000.2630.1110.1210.
  2. 7235. Empiricalanalysis5.1 Benchmarkregressionandtest5.1.1 Benchmarkregressionanalysis Thebenchmarkregressionresultsareshowninthetablebelow:(1\-(3\listtheregressionresultswithfixedeffectsaddedsequentially. Thedigitaleconomydevelopmentlevelofsampleprovincesispositivelycorrelatedwiththemanufacturingsector'sforeigntradecompetitivenessata1%significancelevel, indicatingthatarobustdigitaleconomycansignificantlyenhancethecompetitivenessofmanufacturinginforeigntrade. Thissupports Research Hypothesis
  3. 1. Thedigitaleconomymayboostinternationalcompetitivenessinmanufacturingthroughmeasuressuchasenhancinginformationtechnologyapplication, optimizingproductionprocesses, andimprovingmarketaccess. Thisisespeciallytrueinthecontextofrapidglobalizationandinformatization, wherepromotingthedevelopmentofthedigitaleconomycouldbecomeakeyfactorinstrengtheningmanufacturingcompetitiveness. Table3: Resultsofbenchmarkregressionanalysis VARIABLES(1\(2\(3\TCTCTCDig0.723***0.559***0.445**(4.44\(3.81\(1.99\Open-0.415***0.129*0.307***(-8.61\(1.93\(4.09\Indus1.928***0.622*1.541***(8.00\(1.90\(4.42\Fdi-0.060***-0.004-0.006(-3.38\(-0.29\(-0.48\Res-21.250***0.649-1.354(-7.25\(0.20\(-0.27\Gov-1.060***-0.631**-0.574**(-5.11\(-2.37\(-2.12\Constant1.066***0.094-0.181(3.83\(0.49\(-0.92\Individual Fixed Effects NOYESYESYear Fixed Effects NONOYESObservations300300300R-squared0.4970.9390.947r2_a0.4870.9310.938F72.766.7688.777 Robustt-statisticsinparentheses***p<0.01,**p<0.05,*p<0.15.1.2 Endogeneityandrobustnesstest Toenhancethereliabilityoftheresearchconclusions, thispaperconductsendogeneityandaseriesofrobustnesstests. First, toavoidpotentialendogeneityissuesthatcouldinterferewiththeresearchresults, weusethelaggedone-periodlevelofdigitaleconomydevelopmentasaninstrumentalvariable. Thisinstrumentalvariablepassesthenon-identificationconstrainttest(P-value=0.000\andtheweakinstrumenttest(Wald F=529.862>10%maximal IVsize=16.38\. Theregressionresultsusingtheinstrumentalvariableareshownincolumn(1\, indicatingthatthereisstillapositivecorrelationbetweenthelevelofdigitaleconomydevelopmentandthecompetitivenessofmanufacturinginforeigntradeatthe1%significancelevel. Additionally, wereplacetheindicatorofwhetherthelevelofdigitaleconomydevelopmentexceedstheaveragelevelofallprovincesand International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com70|Pagecitiesinthesameyearwitha0-1variableforre-regression, andperformpropensityscorematchingbasedonthisdummyvariable. Theregressionresultsarepresentedincolumns(2\and(3\, confirmingthesameconclusion. Finally, werandomlyselect80%ofthesamplefortesting, withtheresultsshownincolumn(4\, whichalsoconfirmsthesameconclusion. Insummary, theresearchconclusionsofthispaperarerelativelyrobust, indicatingthatimprovingthelevelofdigitaleconomydevelopmenthelpsenhancethecompetitivenessofmanufacturinginforeigntrade. Table4: Resultsofendogeneityandrobustnesstests Variables(1\IVRegression(2\Replace Explanatory Var.(3\Propensity Score Matching(4\Random Sampling Dig0.796***(2.62\0.070***(3.36\0.068**(2.40\0.777**(2.54\Open0.378***(3.96\0.241***(3.59\0.534**(2.48\0.287***(3.35\Indus1.889***(4.59\1.392***(4.32\2.089***(5.69\1.631***(4.59\Fdi-0.012(-0.91\-0.007(-0.54\-0.052***(-3.28\-0.018(-1.33\Res2.218(0.38\-5.519(-1.16\16.974**(2.18\4.709(0.80\Gov-0.697**(-2.39\-0.553*(-1.94\-0.279(-1.21\-0.557**(-2.10\Constant-1.226***(-4.73\0.040(0.20\-0.130(-0.47\-0.243(-1.10\Individual Fixed Effects YESYESYESYESYear Fixed Effects YESYESYESYESObservations270300161240R-squared0.9510.9470.9610.947 Adjusted R?(r2_a\0.9420.9380.9500.935F-statistic612.49.5618.046 Robustt-statisticsinparentheses***p<0.01,**p<0.05,*p<0.15.2 Testofregulatoryeffect Tofurtherinvestigatethemechanismofhowtheexportstructureofmanufacturingaffectsdigitaleconomicdevelopmentandforeigntradecompetitiveness, basedonthetheoreticalanalysisintheprevioussection, theexportstructureofmanufacturing(Expy\isusedasamoderatingvariable, andaninteractiontermbetweentheindexofdigitaleconomicdevelopmentandtheexportstructureofmanufacturingisintroduced. Regressionusingmodel(2\yieldsresultsshownin Table
  4. 5. Thecoefficientoftheinteractiontermispositiveandsignificantatthe1%level, indicatingthattheexportstructureofmanufacturinghasasignificantpositivemoderatingeffectontheimpactofdigitaleconomicdevelopmentonthecompetitivenessofmanufacturing'sforeigntrade. Thismeansthatwhentheexportstructureofmanufacturingupgrades, transitioningtohigher-value-addedandtechnology-intensiveproducts, thedevelopmentofthedigitaleconomywillhaveamorepronouncedeffectonenhancingtradecompetitiveness. Whentheexportstructureplacesgreateremphasisonhigh-endanddiversifiedproducts, thepromotingroleofthedigitaleconomycanbebetterleveraged, helpingcompaniesimprovetheirmarketadaptabilityandgainafavorablepositioninglobalcompetition. Table5: Testresultsofregulatoryeffects Variables(1\YDig0.036(0.16\Expy-0.107***(-4.12\Dig?Expy0.017***(2.68\Open0.197***(2.79\Indus1.232***(3.44\Fdi-0.007(-0.58\Res-4.737(-0.95\Gov-0.508**(-2.03\Constant1.062***(3.06\Individual Fixed Effects YESYear Fixed Effects YESObservations300R-squared0.952 Adj. R?0.944F-statistic9.239 Robustt-statisticsinparentheses***p<0.01,**p<0.05,*p<0.15.3 Heterogeneityanalysis Duetothesignificantdifferencesindigitaleconomicdevelopmentlevelsandmanufacturingcharacteristicsacrossprovinces, theimpactofdigitaleconomicdevelopmentonthecompetitivenessofmanufacturinginforeigntrademayexhibitregionalheterogeneity. Toexploretheheterogeneouseffectsacrossdifferentregions, thispaperdivides30sampleprovincesintowestern, central, andeasternregionsbasedonexistingresearchandconductsregionalregressionanalysis. Theregressionresultsareshowninthetablebelow: Table6: Resultsofheterogeneityanalysis Variables(1\Western Region(2\Central Region(3\Eastern Region TCTCTCDig-0.562(-0.59\1.268*(1.96\0.420**(2.40\Open0.702(1.34\1.375**(2.48\0.179*(1.90\Indus0.803(0.69\1.636***(4.12\1.827***(3.24\Fdi-0.013(-0.41\-0.040*(-1.98\-0.003(-0.12\Res-15.477(-1.24\13.253*(1.75\12.819*(1.87\Gov-0.597(-1.35\-0.516(-0.76\-0.222(-0.54\Constant0.744(1.19\-0.331(-0.86\-0.814***(-4.16\Individual Fixed Effects YESYESYESYear Fixed Effects YESYESYESObservations9090120R-squared0.8360.9720.983 Adj. R?0.7790.9620.978F-statistic3.1577.9366.036 Accordingtotheresultsinthetableabove, itcanbeseenthatthecoefficientsandsignificancelevelsofdigitaleconomicdevelopmentvaryacrossthewestern, central, andeasternregions, indicatingthattheimpactofdigitaleconomicdevelopmentlevelsonthecompetitivenessofmanufacturinginforeigntradediffersregionally. Theresultsincolumn(2\showthatthecoefficientofdigitaleconomicdevelopmentissignificantlypositiveatthe1%level, indicatingasignificantpositiveeffectofthedigitaleconomicdevelopmentlevelinthecentralregiononthecompetitivenessofmanufacturinginforeigntrade. Asthedigitalinfrastructureinthecentral International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com71|Pageregionbecomesincreasinglycompleteanddigitaltechnologiesaremorewidelyadopted, thegrowthrateofthedigitaleconomyisfast, anditiscurrentlyinaperiodofbenefitingmanufacturingthroughdigitalization. Moreover, themanufacturingindustryinthecentralregionisatacriticalstageoftransitioningfromlabor-intensivetotechnology-intensive, andtheintroductionofthedigitaleconomycanimproveproductionefficiencyandreducecosts, therebyfurtherenhancingthecompetitivenessofforeigntradeinthecentralregion.
  5. 6. Conclusionsandrecommendations Thispaperisbasedonpaneldatafrom30provincesin Chinabetween2012and
  6. 2021. Itemploysbidirectionalfixedpaneleffectmodelsandmoderationeffectmodelstoconductmultidimensionalempiricalanalysisoftheimpactofdigitaleconomicdevelopmenton China'smanufacturingexportcompetitivenessandthemoderatingeffectofmanufacturingexportstructure. Themainconclusionsdrawnfromthisstudyareasfollows: First, anincreaseinthelevelofdigitaleconomicdevelopmentcansignificantlyenhance China'smanufacturingexportcompetitiveness; thepromotioneffectofdigitaleconomicdevelopmentonmanufacturingexportcompetitivenessischaracterizedbycentralregions>easternregions>westernregions. Second, whenthemanufacturingexportstructureisupgraded, theimprovementinthelevelofdigitaleconomicdevelopmenthasamoresignificantimpactontradecompetitiveness, withapositivemoderatingeffect Basedontheaboveconclusions, thispaperproposesthefollowingrecommendations: First, continuouslypromotethedevelopmentofthedigitalindustrytoenhancecompetitivenessinforeigntrade. Byimprovingdigitalinfrastructure, drivingthedigitaltransformationofmanufacturing, optimizingpolicyenvironments, andpromotingdeepintegrationbetweenthedigitaleconomyandtherealeconomy, wecanpromotehigh-qualitydevelopmentinmanufacturing, effectivelyboost China'sinternationalcompetitivenessinmanufacturing, andhelp Chinatransitionfroma"manufacturinggiant"toa"manufacturingpowerhouse."Second, basedonregionaldifferencesinthelevelofdigitaleconomicdevelopment, formulaterelevantcoordinateddevelopmentpaths. Theeasternregionshouldfocusonthedeepdevelopmentandinnovationofthedigitaleconomy, promotingtheintegrateddevelopmentofadvancedmanufacturinganddigitalservices, furtherexpandingitsinternationalinfluence; thecentralregionshouldprioritizetheconstructionofdigitalinfrastructure, assistingtraditionalmanufacturinginitsdigitaltransformation, leveragingexistingadvantagestoformanewpatternofcoordinateddevelopmentbetweenthedigitaleconomyandmanufacturing; thewesternregionshouldincreaseinvestmentindigitalinfrastructure, usinglate-moveradvantagestonarrowthegap, anddevelopnewmodelsofgreenmanufacturinganddigitaleconomyintegrationbasedonresourceendowments. Third, leveragetheregulatoryroleofmanufacturingstructureupgradestopromotetheupgradingofexportstructuresandthedeepintegrationofthedigitaleconomy. Atthegovernmentlevel, thereshouldbeincreasedpolicysupportforhigh-techandhigh-value-addedmanufacturing, improvingdigitalinfrastructure, andencouragingandguidingenterprisestotransformintohigh-endmanufacturingsectors; attheenterpriselevel, theyshouldusethedigitaleconomytoadvancetheoptimizationandupgradingofexportstructures, utilizingbigdata, artificialintelligence, andothertechnologiestooptimizeproductionprocesses, improveproductquality, andenhanceinternationalcompetitiveness References
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Publication Information

Journal: International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE)

Publisher: Anfo Publication House

ISSN: 2582-7138 (Online)

Frequency: Bimonthly

Language: English

Open Access: Yes - This article is distributed under the terms of the Creative Commons Attribution 4.0 International License

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